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New today · July 27, 2026
What the posting requires: - 0 to 1 years in software development, ideally with internships in integrations or data tools. This is the stated candidate persona and it is the reason this role is on the list. - A B.Tech in Computer Science or equivalent from a reputed college. This is stated in the posting. - Basic object oriented programming skills and familiarity with design principles. - Exposure to data pipelines or APIs, and eagerness to learn concurrency and performance basics. - Foundational knowledge of REST APIs, for example making calls and handling JSON. The posting says explicitly that no deep expertise is needed here. - Proficiency in Java, TypeScript or Python, with good problem solving using data structures and algorithms. - Strong analytical and logical thinking for real world challenges. What the work actually looks like: - Implement SaaS connectors for assigned applications, learning application specific nuances such as basic auth and data extraction. - Assist in building simple REST API components, focusing on clean implementation and testing. - Debug and optimise code for data pipeline efficiency, under mentorship. - Contribute to feature breakdown, coding and documentation for smaller tasks. - Apply logical thinking to solve integration issues and improve component quality. What this tells you about the role: the words under mentorship and assist appear in the responsibilities, which is a good sign for a first job. You are not being asked to own a system alone. The work is connector and integration engineering, which is a real specialism and a useful one, since almost every SaaS company needs people who can make two systems talk to each other. About the company: Hevo is based in San Francisco and Bangalore, powers data analytics for more than 2,000 companies across 45 plus countries, and states its mission as building technology from India for the world that is simple enough that anyone can unlock the potential of their data. Location and working pattern: Bengaluru. Office days are not stated. Honest fit guidance: if you are a recent graduate or in your first year, this is the role on today's list to spend your best application on. The degree requirement from a reputed college is stated explicitly, so know that going in if your background is non traditional. Prepare by being able to talk about an API you have consumed and a data problem you have debugged, because that is exactly what the responsibilities describe. No interview process is published.
What the posting requires: - A Bachelor's or Master's in Computer Science, Engineering or a related field, with 5+ years of enterprise integration experience. - At least 3 years of integration development using platforms such as Workato, MuleSoft or Boomi. - Deep understanding of enterprise integration design patterns, messaging and event driven architectures, plus Workato concepts including callable recipes, event streams and task optimisation. - Proficiency with Workato connectors including Salesforce, NetSuite, HRIS and Google Workspace, along with Python or Ruby scripting. - Strong development experience implementing Workato at scale: automation, observability and monitoring, and debugging in complex environments with many connected systems, plus DevOps process adhering to compliance, audit and internal CI/CD. - Hands on experience implementing secure and scalable REST APIs, and implementing Workato MCP and agentic workflows. - Strong problem solving and debugging across multiple connected systems and their environments. - Excellent analysis and design ability, with focus on system design, flow, scalability and performance, and mapping business requirements to technical solutions. What the work actually looks like: - Automate, develop and support integrations across various business systems, platforms and tools. - Work with different business units and technical teams to gather requirements and design solutions. - Create scalable solutions and operationalise integrations. - Implement and promote integration best practices. - Participate in an on call support rotation. The success measures the employer publishes: - Deliver high quality, scalable integration recipes and flows within the Quote to Cash process and other GTMTech programmes, on time. - Successfully deploy and operationalise integrations while keeping system stability and performance. - Proactively identify and resolve complex integration issues with minimal disruption to core business operations. - Translate complex requirements into technical design with business and technical teams. Location and working pattern: the posting states MongoDB wants candidates based in Gurugram for its hybrid working model. Honest fit guidance: the Workato requirement is specific and enforced, so this suits an integration specialist rather than a general backend engineer. If you have built on MuleSoft or Boomi the transferability is real. The on call rotation is stated, so factor it in.
What the posting requires: - 5+ years of experience in analytics or data science, with a strong track record of solving ambiguous business problems. - Functional expertise building analytical solutions, and the ability to be a trusted partner to business teams and leaders through insights and recommendations. What the work actually looks like: - Build agentic analytics pipelines that automate insight generation across key metrics including contact volume, handle time and resolution quality. - Develop reusable skill libraries: composable agent tools such as volume lookups, NPS pulls and handle time calculations, callable across workflows and teams. - Design and govern prompt templates and playbooks: standardised, governed prompts for recurring analytical questions, for example what drove contact volume this week. - Build orchestration workflows: multi step pipelines that chain skills together to produce automated insight narratives and proactive alerts without manual intervention. - Deploy self serve interfaces that let non technical people query certified data independently. - Ship rapid, prompt driven dashboards that compress the cycle from business question to live view. - Automate business reviews with scheduled, agent generated summaries of key metrics. - Build and maintain evaluation and observability frameworks for those systems. Who you would work with: business and operational leaders across Airbnb's Community Support organisation, sitting under the Advanced Analytics family within the Analytics Centre of Excellence. What the team does more broadly: the ACOE delivers metrics, dashboards, performance optimisation, pre and post feature impact measurement, opportunity sizing, anomaly driven alerting, root cause analysis of metric deviation and exploratory hypothesis testing. Location and working pattern: Gurugram, India. This is the Gurugram based role, not a remote one. Honest fit guidance: read the AI framing as real rather than decorative. The responsibilities are almost entirely about building agentic tooling and self serve interfaces, not producing analyses by hand. If your analytics experience is SQL and dashboards with no agent or LLM tooling, that is the honest gap. If you have been building with agents and want an analytics seat where that is the job rather than a side project, this is a strong match at 5 years.
What the posting requires: - A Bachelor's degree in Computer Science, Engineering or a related field. - 5+ years of professional Java development experience with Spring, JDBC, and MyBatis or Hibernate or equivalent. - Experience with application modernisation, database migrations or large scale refactoring initiatives. - Strong SQL expertise: you can analyse, interpret, optimise and rewrite complex SQL embedded in Java applications. - Deep understanding of JDBC, ORMs, Java transaction patterns and database driven application flows. - Experience on enterprise grade, high performance applications with complex data interactions. - Strong communication skills and the ability to work with globally distributed teams in US time zones. Nice to have: - Experience with PostgreSQL or Aurora PostgreSQL, or modernisation from legacy databases such as Oracle, SQL Server or DB2. - Exposure to automated code refactoring tools or GenAI assisted remediation workflows. - Familiarity with CI/CD environments, performance testing tools and observability stacks. - Consulting or professional services experience delivering fixed timeline modernisation projects. What the work actually looks like: - Analyse and remediate large enterprise Java codebases, replacing legacy and database specific SQL constructs with modern, standards compliant SQL. - Convert embedded SQL in Java services and MyBatis XML mappers: vendor specific functions, sequences, pagination logic, dynamic SQL and error handling patterns. - Work with schema and database migration engineers so application layer SQL lands aligned with the modernised target schema. - Refactor Java transaction logic, error handling, drivers and ORM or DAO layers. - Run unit, integration and performance testing to confirm functional parity and hit performance SLAs after modernisation. - Support production cutover: validation, monitoring setup, rollback planning and stabilisation until the system holds. - Produce engineering documentation that outlives the engagement: SQL remediation guides, code migration runbooks, troubleshooting guides and knowledge transfer material. What the company says about how the work splits: the agent platform does the repetitive 60 to 70 percent that a traditional consulting engagement would staff humans for, including mechanical SQL conversion and the regression harness. Your hours go to the refactoring judgement. Location and working pattern: Mumbai, with distributed collaboration across US and India teams and an expectation of overlap with US time zones. Honest fit guidance: this is deep, unglamorous, high value work. If you have lived inside a large Java codebase with vendor specific SQL, five years is enough. If your Java is greenfield microservices only, the legacy remediation requirement is the gap.
What the posting requires as mandatory: - Experience of 5 to 8 years for the Staff level, or 9 to 12 years for the Sr Staff level. One posting, two levels, so read the band that matches you. - Strong programming experience in Java. - Strong computer science fundamentals, especially algorithms, data structures, object oriented programming and SQL. - Hands on experience with Spring and Spring Boot, and ORM frameworks. - Good understanding of database internals and schema design across different data stores, both relational and NoSQL. - Experience designing and developing APIs for large scale data systems with low latency. - Experience working in a client server, cloud hosted environment. - Strong analytical and problem solving skills. Good to have: - Experience with AWS, described as highly desirable. What the work actually looks like: Device health and monitoring: - Understand IoT devices and accessories to build and enhance device monitoring and health solutions. - Develop systems for device health monitoring covering camera, LTE, GPS, storage, power, real time clock and accessories. - Implement device online and offline detection and recovery mechanisms. - Design health state transitions and root cause classification for device issues. Backend and platform: - Design, develop and maintain high performance, reliable, reusable backend services. - Build and test large scale SaaS products processing massive volumes of real time data. - Build and operate systems processing hundreds of millions of IoT sensor events per day. System design and ownership: - Translate product requirements into technical designs and tasks, and execute across the full development lifecycle. - Design APIs with low response times and efficient resource use for large data sets. - Provide technical guidance and mentorship to junior engineers, and debug complex issues to root cause. ⚠️ Location and working pattern, stated explicitly: Whitefield, Bangalore, **on site 5 days a week**, general shift or evening shift. Netradyne is one of the few employers on this board that publishes its office policy, and this one is fully in office with a possible evening shift. Factor that in before applying. A note on the employer: Netradyne postings carry a recruitment fraud warning. Official communication comes only from netradyne.com or us-greenhouse-mail.io addresses, and the company never charges candidates a fee. Honest fit guidance: if you have 5 to 8 years of Java backend work at scale, apply to the Staff band rather than being put off by Sr Staff in the title. IoT domain experience is not required, but comfort with high volume event processing is.
What the posting requires: - 5 to 10 years of experience in field engineering, enterprise deployment or senior IT support roles. - Deep, hands on expertise with Intune and SCCM covering policy design, compliance management and large scale fleet deployment. The posting marks this **non negotiable**. - Advanced PC hardware diagnostics across BIOS, firmware and hardware level troubleshooting on varied enterprise device configurations. Also marked **non negotiable**. - Strong PowerShell scripting, with the ability to build and maintain automation frameworks for enterprise environments. - Expert level knowledge of Windows OS in enterprise and managed fleet contexts. - A proven track record in customer facing technical roles, comfortable engaging enterprise IT leadership. - Experience owning SLA management and escalation governance across multiple enterprise accounts. Bonus points: - Prior experience with on device AI, edge computing or sovereign enterprise AI deployments. What the work actually looks like: - Lead deployment and configuration of Sarvam's on device AI platform across large enterprise PC fleets using Intune and SCCM. - Own escalated hardware diagnostics, resolving complex BIOS, firmware, driver and hardware level issues. - Architect and maintain PowerShell automation frameworks for deployment, monitoring and configuration management at scale. - Define and enforce MDM policy architecture via Microsoft Intune. - Drive presales engagements: technical discovery, scoping proof of concept deployments, and presenting to enterprise IT leadership. - Own SLA governance across a portfolio of enterprise accounts, managing escalations and resolution quality. - Act as primary technical liaison between enterprise customers and Sarvam's product and engineering teams. - Build and maintain deployment playbooks, technical runbooks and support documentation. - Mentor and guide other field engineers. What makes the context unusual: the posting describes the team as co owning the most ambitious on device AI problem in India, building sovereign models that run at the silicon level, embedded with partners including Qualcomm, Intel, HP, Apple and NVIDIA. Location and working pattern: Bengaluru, described as on site or hybrid, with significant customer facing and mentoring responsibility. Honest fit guidance: this is enterprise endpoint engineering more than it is AI engineering, and the two non negotiables tell you where applications will be judged. If your background is Windows fleet management at scale and you want to work at an AI company, it is a rare bridge. If you want to build models, this is not that role.
What the posting requires: - 5 to 8 years in field engineering, solutions engineering, technical account management or senior client facing engineering roles. - Strong Python proficiency, with the ability to read, debug and contribute to production FastAPI services and ML pipelines. Marked **non negotiable**. - Experience with audio and video processing workflows: FFmpeg, codec pipelines, media formats or streaming infrastructure. Also marked **non negotiable**. - A proven track record working with enterprise media, OTT or content localisation clients. - Comfort operating across the stack: REST APIs, async job queues such as Celery or Redis, PostgreSQL, cloud storage on Azure, GCP or AWS, and Kubernetes. - Strong debugging instincts, tracing failures across distributed systems from API through queue and worker to ML inference and storage. - Experience owning SLA management and escalation governance across multiple enterprise accounts. - Excellent communication, comfortable engaging CXO and VP level stakeholders. What the work actually looks like: - Lead end to end integration of the dubbing platform into enterprise content workflows across OTT, media houses, ed-tech and enterprise learning and development. - Own the technical relationship with strategic accounts: scoping requirements, designing integration architecture and ensuring production readiness. - Debug and resolve complex pipeline issues across the full dubbing stack: audio separation, speech recognition, translation, text to speech and video stitching. - Tune pipeline parameters for client specific content: voice activity detection thresholds, translation glossaries, TTS voice profiles and audio mixing. - Drive presales engagements including technical discovery and proof of concept scoping. - Build and maintain integration playbooks, API guides and troubleshooting runbooks. - Define SLA governance across enterprise accounts covering turnaround time, quality benchmarks and escalation resolution. - Act as primary technical liaison between enterprise clients and Sarvam's dubbing product and ML engineering teams. - Mentor other field engineers, and contribute fixes back to internal platform codebases when client deployments surface bugs. Location and working pattern: Bengaluru, with significant customer facing responsibility. Honest fit guidance: the media pipeline experience is the differentiator. Plenty of engineers can debug a distributed system, far fewer have worked with FFmpeg and codec pipelines, and that is what the posting marks non negotiable alongside Python. If you have both, the customer facing element is learnable. If you have neither, the title being FDSE will not carry the application.
What the posting requires: - 6 to 9 years of software development experience with enterprise grade software. - Experience building scalable, high performance cloud services. - Expert coding skills in Scala or Java backend. The product is built in Scala on the Lightbend stack with Play and Akka. - Deep knowledge of databases, query optimisation and views. - Development on cloud platforms including AWS. - Expertise building scalable, event based asynchronous systems on a microservices architecture. - Experience with Docker and Kubernetes. - Expertise building REST APIs. - Cybersecurity experience and adversarial thinking. - Willingness to learn, challenge yourself and share ideas with the team. - Ability to multitask across roles in a fast paced environment: leading a feature design one week, fixing a critical bug or improving CI the next. - A BSCS or equivalent is required, MSCS or equivalent strongly preferred. What the work actually looks like: - Work with the engineering team to design, build and test the cloud based platform across front end, back end and services. - Participate in feature estimation and prioritisation, sprint planning, biweekly sprints, code reviews and retrospectives. - Contribute to product development: understand customer needs and work with product to design, plan and implement new features. - Support early customers by investigating and fixing production issues. - Improve processes and make the right tradeoffs between agility, cost and reliability. Levelling, which matters here: the posting states this team is hiring across all levels and that candidates are individually assessed and levelled based on their skills and experience. So the Staff in the title is not a hard floor. Location and working pattern: listed as India without a specific city. Netskope has a Bangalore office and describes open desk layouts, so confirm the base location with the recruiter. Honest fit guidance: the Scala requirement is the real filter. Netskope will take strong Java backend engineers, since the posting says Scala or Java, but the codebase is Scala on Play and Akka and you would be working in it daily. If you have wanted an excuse to work in Scala at scale on a security product, this is one of the few such roles in India. The early team member framing means less structure than a mature team.
What the posting states: - Experience required: 6 to 9 years. - Native Android and iOS development. The title specifies both platforms rather than one, so cross platform depth is the expectation rather than a single specialism. - Employment type: full time. What the work involves, based on the role and the product: building and maintaining the native mobile applications through which fleet customers and drivers interact with Netradyne's driver monitoring and safety scoring platform, working alongside the backend, embedded and analytics teams that produce the data those apps display. ⚠️ Location and working pattern, stated explicitly in the posting: Whitefield, Bangalore, **on site 5 days a week**, general shift or evening shift. This is one of the few postings on today's board that publishes its office policy precisely. If you need hybrid or remote, this role is not it, and the evening shift possibility is worth clarifying at first contact. About the employer: Netradyne provides AI powered technologies for fleet management and road safety, is an award winning leader in fleet safety and video telematics, and serves thousands of commercial fleet customers across North America, Europe and Asia. Founded in 2015, headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore. The company reports growth exceeding 4x year over year. A note on the employer: Netradyne postings carry a recruitment fraud warning. Official communication comes only from addresses ending in netradyne.com or us-greenhouse-mail.io, the company never requests sensitive personal data over text or unsecured channels, never promises advance payment for work equipment, and never uses agencies that charge candidates a fee. Honest fit guidance: this posting is thinner on detail than most on today's list, so treat the 6 to 9 years and the dual platform requirement as the firm parts and ask the recruiter about scope, team size and what the apps actually do. The office policy is the clearest signal in it and it is a strict one. If you are a native mobile engineer in Bangalore who is fine with full time office work, the product is more interesting than most: real vehicles, real safety outcomes, real scale.
What the posting states: - Job title: Staff Engineer, Embedded System Engineer. - Department: Device. - Experience: 6 to 12 years. That is a wide band in a single posting, so treat 6 as the real floor. What the work involves, based on the department and product: embedded software for Netradyne's edge devices, the camera units that run computer vision on the vehicle itself rather than in the cloud. That work sits alongside the company's other device roles covering multimedia pipelines, middleware on Linux, board support package development and hardware engineering, all of which Netradyne staffs separately, so expect a specialised slice rather than the whole device stack. Location and working pattern: Bangalore. This particular posting does not state the number of office days, though several other Netradyne listings specify on site five days a week at Whitefield. Ask rather than assume, because the company's other device roles are explicitly full time in office. About the employer: Netradyne provides AI powered technologies for fleet management and safer roads, is an award winning industry leader in fleet safety and video telematics, and empowers thousands of commercial fleet customers across North America, Europe and Asia. It sets its standard on 25 plus billion miles vision analysed for risk and an industry first driver scoring system. Founded in 2015, headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore. A note on the employer: Netradyne includes a recruitment fraud warning in its postings. Official communication comes only from netradyne.com or us-greenhouse-mail.io addresses, the company does not request sensitive personal data via text or unsecured channels, does not promise advance payment for equipment setup, and does not use agencies that charge candidates a fee. Honest fit guidance: this posting is light on a requirements list, which cuts both ways. It means fewer boxes to fail on, and it means you should ask early which part of the device stack the role covers, since Netradyne runs separate reqs for multimedia, middleware, BSP and hardware. If you have shipped embedded software on Linux based devices and want work where the constraint is real hardware rather than cloud cost, six years is enough to be taken seriously here.
What the posting requires as minimum qualifications: - A minimum of 6+ years of experience in technical support, with at least 4 years focused on DLP and CASB solutions. - A foundational understanding of AI and ML technologies, and experience leveraging, securing or positioning AI driven solutions within your functional domain. Zscaler lists this first. - Experience with data loss prevention, securing SaaS, and Cloud Access Security Brokers. - Practical working knowledge of AWS, Azure or GCP cloud environments, paired with a strong understanding of Unix, Linux and Windows operating systems. - Deep understanding of data protection principles and practices. Preferred qualifications: - Experience deploying or supporting AI powered sensitive data discovery tools or automated data classification models to enhance DLP capabilities. - Experience with scripting and automation using Python or PowerShell. - Knowledge of regulatory requirements and compliance standards such as GDPR, HIPAA or PCI DSS. What the work actually looks like: - Provide advanced troubleshooting and resolution for complex DLP issues raised by enterprise customers. - Perform root cause analysis to identify underlying problems and implement lasting solutions. - Work with product development, engineering and other cross functional teams to resolve issues and improve Zscaler's DLP products. - Maintain clear and proactive customer communication through the support process. How this compares to the neighbouring role: Zscaler also lists an Escalation Engineer DLP requiring 8+ years with at least 5 on DLP. Same specialism, one level up. If you sit between 6 and 8 years this posting is the better fit, and the escalation one is a natural next step. Location and working pattern: Bangalore or Mohali. Zscaler's DLP postings are described as hybrid roles based in those offices, reporting into Product Support. What Zscaler says about its culture: impact over activity, constructive and honest debate, customer obsession, ownership and accountability, with an emphasis on using AI to amplify individual impact. Honest fit guidance: the 4 years specifically on DLP and CASB is the filter, not the 6 years overall. General cloud support experience will not clear it. Support engineering at this tier is genuinely technical work with direct engineering contact, but be clear eyed that it is a support function with the customer communication load that implies.
What the posting requires: - A BS or higher in Computer Science, or a related field. - 7+ years of production level experience in one of Java, Scala, C++ or a similar language. - Comfort working towards ambitious goals in a fast moving environment. - Experience developing large scale distributed systems. - Hands on experience developing and operating backend systems. What the work actually looks like, given the team's remit: - Build and operate the platform systems behind usage metering, billing and revenue for Databricks. - Solve real business needs at large scale through software engineering. - Contribute across project phases from design and development through implementation and ongoing operations. - Investigate and help prevent production issues, since correctness in this domain is directly customer visible. Why this kind of team is worth considering: money and billing systems are usually the highest correctness bar in a company. The data volumes are the same as the rest of the platform, but the tolerance for error is far lower, which tends to mean strong engineering practice, good testing culture and clear ownership. Location and working pattern: Bengaluru. Databricks says it is in the process of setting up new teams from scratch at this site, so expect an in office or hybrid arrangement. The exact number of days is not stated in the posting. Compliance note in the posting: where a role requires access to export controlled technology or source code, Databricks states that applying for a US government licence is at its discretion, and it may decline to proceed with an applicant on that basis alone. Worth reading before investing time in the process. Honest fit guidance: seven years of real production backend work is the bar, and the language list is broad enough that the specific language matters less than the scale you have operated at. If you have worked on billing, metering, payments or any system where a wrong number is a customer incident, say so prominently in your application, because that is exactly the experience this team is buying.
What the posting requires: - 7+ years of experience in information security, with at least 5 years focused specifically on endpoint security engineering. - Deep hands on expertise with enterprise EDR platforms. The posting names CrowdStrike Falcon, Microsoft Defender for Endpoint, SentinelOne and Carbon Black. - Strong experience deploying, managing and tuning enterprise DLP solutions. Named examples are Microsoft Purview, Symantec DLP and Cyberhaven. - Demonstrated experience in insider threat detection and response, including familiarity with UEBA tools and behavioural analytics. Nice to have: - Experience with hybrid cloud environments across AWS, Azure and GCP. - Prior experience in the EV, automotive or critical infrastructure industry. What the work actually looks like: - Lead insider threat detection and response: build and maintain detection logic, investigate anomalous user behaviour, and drive incident response for insider threat cases. - Manage and mature the enterprise data loss prevention programme: define and refine DLP policies, monitor alerts, investigate violations and coordinate remediation with stakeholders. - Own end to end management of the enterprise EDR platform across Windows, macOS and Linux endpoints, covering deployment, policy configuration, tuning and ongoing optimisation. ⭐ Location and working pattern: the posting states **Gurgaon or remote**. That makes this the only role on today's board with a remote option, which matters if relocation is what stands between you and a job. The posting does not elaborate on what remote means in practice, so confirm the expectation, including any travel or occasional office days, before assuming it is fully remote. About the employer: ChargePoint has focused since 2007 on making the transition to electric easy for businesses, fleets and drivers, and operates hardware, software and mobile solutions across North America and Europe. Honest fit guidance: the 5 years specifically on endpoint security is the real filter rather than the 7 years overall. This is corporate security engineering, so if you want product security or application security work this is a different discipline. ChargePoint states it provides reasonable accommodations throughout the hiring process and publishes an email address for accommodation requests.
What the posting requires: - 7 to 10 years of experience in FP&A systems, enterprise performance management or enterprise planning implementations. - Hands on experience in at least one platform: Pigment (preferred), Anaplan, or Workday Adaptive Planning. - Strong understanding of financial planning processes and financial statements, annual sales planning, and driver based modelling and forecasting. - Experience with ERP systems, NetSuite preferred. - Experience with CRM systems, Salesforce preferred. - Experience with data warehouses. Additional technical skills: - Exposure to Python or scripting is described as a plus. - Experience with ETL and integration tools. Preferred qualifications: - Certifications: Anaplan Certified Model Builder or Solution Architect, Workday Adaptive Planning certification, or Pigment Modeler experience. - Experience supporting SaaS or consumption based business models. - Exposure to headcount and compensation planning, annual sales planning, and revenue modelling covering ARR, churn and expansion. - Experience working in a Global Capability Centre or offshore delivery model. What the work actually looks like: Enterprise planning delivery: - Design and build scalable planning models across financial planning (profit and loss, cash flow, balance sheet), workforce planning and cost modelling, and sales and revenue forecasting (ARR, pipeline, bookings). - Own end to end delivery working with the product manager: design, build, test, deploy and support. Model development and optimisation: - Build multi dimensional, driver based models with a strong focus on performance. - Develop scenario planning, versioning and forecasting capabilities. - Optimise model size and calculation performance. Location and working pattern: the posting states MongoDB is looking for candidates based in Bengaluru or Gurugram for its hybrid working model. Honest fit guidance: be clear with yourself about what this is. It is a specialist enterprise planning platform role, closer to FP&A systems work than to backend software engineering, and the certifications listed under preferred qualifications tell you the discipline it belongs to. If you have built models in Anaplan, Pigment or Adaptive Planning, this is a strong senior seat at a well known technology company. If you are a software engineer hoping this is a finance flavoured coding job, it is not.
What the posting requires as mandatory: - A B.Tech, M.Tech or PhD in Computer Science, Electrical Engineering, Statistics, Mathematics or a related field. - 8+ years of experience in data science, analytics or a closely related domain. - Strong foundation in probability, statistics and estimation theory. - Strong programming in Python, with solid fundamentals in object oriented programming, algorithms and data structures. - Deep familiarity with SQL, complex query writing, indexing and database internals, plus working knowledge of at least one NoSQL store. - Experience with data visualisation and analytical storytelling. - Excellent written and verbal communication. - Familiarity with AI powered tools for analytics and software development, including using them for exploratory analysis, experiment analysis and documentation, and critically evaluating AI generated output for correctness, statistical validity and reproducibility. Preferred skills: - Exposure to cloud platforms and services such as AWS Kinesis, EKS and autoscaling systems. - Experience building lightweight web or service components with Flask or Django. - Prior experience with large scale, noisy, real world datasets. What the work actually looks like: - Design, implement and maintain offline and online evaluation frameworks for AI and ML features. - Define, validate and evolve the KPIs, success metrics and audit methodologies used across teams. - Perform deep error analysis, bias analysis and segmentation to identify failure modes. - Own golden datasets, validation protocols and benchmarking standards. - Conduct large scale analytical studies on feature performance, data quality and system behaviour. - Design and review experiments including offline evaluations, controlled rollouts and A/B tests, ensuring statistical correctness. - Perform post deployment monitoring and regression detection. - Build tools, dashboards and automation to scale audits and reporting. - Mentor junior data scientists on statistical rigour, experiment design and analytical storytelling. How this differs from the 5+ years version of this role published on this board on 2026-07-26: same team and same responsibilities, but this posting sets the bar at 8+ years rather than 5+. If you are between 5 and 8, look for the other one. Location and working pattern: Bangalore. This posting does not state office days, though other Netradyne listings specify five days on site. Honest fit guidance: if you want to build models, this is explicitly not that role. It suits someone happier proving whether a system works than building it, and willing to tell a product team its metric is wrong.
What the posting requires: - 8+ years of production level experience in one of Python, Java, Scala, C++ or a similar language. - 4+ years of experience in a networking focused context, which is the specialism this role is hiring for. - Experience developing large scale distributed systems. - Hands on experience developing and operating backend systems. What the work actually looks like, given the team's remit: - Build and operate the networking layer for a platform running across AWS, Azure and GCP at a fleet size measured in millions of virtual machines. - Handle the differences between cloud providers' networking primitives, and design so that provider level faults degrade gracefully rather than breaking customer workloads. - Low level systems debugging and performance measurement on large production clusters. - Contribute across the project lifecycle from design through implementation and ongoing operation. The operating context Databricks describes: at its scale the company routinely observes cloud hardware, network and operating system faults, and the software is expected to shield customers from all of them. That is the daily reality of a networking role there rather than an abstract claim. Location and working pattern: Bengaluru. Databricks says it is standing up new teams from scratch at this site, so expect an in office or hybrid arrangement, with the number of days not stated. Compliance note in the posting: the standard Databricks export controlled technology clause applies. Where such access is required, applying for a US government licence is at the employer's discretion and it may decline to proceed on that basis. Honest fit guidance: the 4 years of networking experience is what separates applications here, not the 8 years overall. Cloud networking at multi provider scale is a narrow skill and the people who have it are usually not looking, which is a reason to apply if you do. If your networking exposure is configuring a VPC occasionally, the requirement is deeper than that.
What the posting requires: - 8+ years of experience building distributed systems and/or foundational cloud services at scale, with an interest in working with Python, Go and Java. - A strong background building core components for high scale compute and data distributed systems. - Proven success in designing, writing, testing, debugging and performance tuning, with a strong grip on computer science fundamentals, and maintaining distributed or highly concurrent software in large, long lived codebases. - A track record of identifying problems and implementing solutions. - Eagerness to learn, with a strong technical background. - The ability to be a force multiplier in the software development process, enabling teams to deliver through leadership and technical contribution. Bonus points: - Experience with containerisation and orchestration platforms such as Kubernetes. - Experience with AI frameworks and tools. What the posting sets as position expectations: - Work closely with research, product management, product engineering, product design and other teams to define the first version and future evolution of the service. - Design, build and deliver well tested core pieces of the platform in collaboration with other stakeholders. - Contribute to shaping architecture, code reviews, development practices and developer experience as the teams and product grow. - Mentor fellow engineers and assume ownership and accountability of projects. What kind of role this is: defining the first version of a service means less existing structure and more influence over how it is built. That is attractive if you want architectural ownership and frustrating if you prefer a mature codebase with settled patterns. Location and working pattern: the posting states MongoDB is looking for candidates based in Gurugram for its hybrid working model. Honest fit guidance: eight years is a real bar here because the role is about judgement as much as output. The distinguishing experience is having maintained distributed systems in large, long lived codebases, which is different from having built greenfield services that never had to survive five years. If you have both, say so.
What the posting requires: - 8+ years of software engineering experience, described as being a master of fundamentals. This is the E4 level; Instawork also lists an E3 version of the same role at 6+ years. - Full stack versatility: able to move between frontend, backend and infrastructure and own features end to end. - Comfort designing user experience in React and diving into AWS to tune heavy video transcoding pipelines. - Ability to architect and scale cloud environments, including complex AWS infrastructure and ECS services. - Deep observability practice with precise telemetry across CPU, memory, network and disk IOPS. - Ability to design and optimise data pipelines at scale. - Strong engineering intuition and architectural expertise. The team leverages agentic coding models heavily and says it relies on human judgement to keep systems robust and built the right way. What the work actually looks like: - Own the technical execution for massive scale physical AI training data. - Lead technical development of the global data collection platform and the dedicated quality assurance platform, ensuring high throughput data enrichment, labelling and continuous quality assurance loops. - Architect and scale cloud environments, managing AWS infrastructure and ECS services for video transcoding. - Design and optimise data pipelines capable of operating at scale. - Act as a key engineering leader in the Bengaluru hub. What the business actually does, since it is unusual: Instawork Robotics Labs deploys skilled hourly workers into real commercial and residential environments to capture task data, which robotics labs then use to train foundation models. The posting frames closing that data gap as the defining infrastructure challenge of the physical AI era. Location and working pattern: Bengaluru. Office days are not stated. Honest fit guidance: the posting asks for a generalist and means it, so specialists who have worked in one layer will struggle against the breadth requirement. Video pipeline and transcoding experience is the part most candidates lack. If you are between 6 and 8 years, apply to the E3 posting instead of stretching for this one, since both are open.
What the posting requires as minimum qualifications: - A foundational understanding of AI and ML technologies, and experience leveraging, securing or positioning AI driven solutions to optimise outcomes within your functional domain. Zscaler lists this first. - 8+ years of support and networking experience as a subject matter expert specialising primarily in Zscaler Client Connector technologies. - Expertise in networking, cloud security and performance management, with the ability to quickly master new technologies. - Proven effectiveness at collaborating and building consensus across cross functional teams and organisations. - Experience developing new processes, tools or product features. What the work actually looks like: - Act as the deep subject matter expert on client connector technology for the wider support and engineering organisation. - Develop new processes, tools and product feature input rather than only resolving individual cases, which is what distinguishes a Center of Excellence seat from escalation work. - Collaborate across support, engineering and product to drive consistent outcomes. What Zscaler says about the environment: an AI forward enterprise built around the world's largest security data lake powering its cloud native Zero Trust Exchange platform. Culturally it emphasises impact over activity, constructive and honest debate, customer obsession, ownership and accountability, and a bias toward speed with quality. Location and working pattern: Bangalore or Mohali. Zscaler's support organisation roles in these locations are generally hybrid, though this particular posting does not spell the arrangement out, so confirm it. Honest fit guidance: the specialism is narrow and named. If you have spent years on Zscaler Client Connector or a directly comparable endpoint agent in a security platform, that specific depth is what is being bought and the 8 years is a fair reflection of it. If your background is general network support without that agent level depth, the requirement is more specific than it first appears. The process and tooling development part of the role is worth weighing positively: it is what makes this more than a support ladder step.
What the posting requires as minimum qualifications: - A foundational understanding of AI and ML technologies, and experience leveraging, securing or positioning AI driven solutions to optimise outcomes within your functional domain. - 8+ years of experience in customer facing technical roles such as professional services consulting. What the work actually looks like: - Serve as a dedicated technical advisor for strategic enterprise customers over extended engagements, described in the posting as six months, one year or longer. - Act as the customer's go to expert for all matters relating to their Zscaler environment. - Work embedded within the customer's organisation rather than rotating across many accounts. How this differs from Zscaler's other customer facing roles on this board: escalation engineers handle the hardest cases across many customers as they arrive, and Center of Excellence engineers build the tooling and processes behind them. A resident consultant is assigned to one customer for a long stretch. Same product depth, very different day to day rhythm and relationship. What Zscaler says about the environment: an AI forward enterprise, cloud native Zero Trust Exchange platform, with a culture it describes around impact over activity, honest debate, customer obsession and accountability. Location and working pattern: Mumbai. Resident consulting typically means significant time at the customer site, so clarify what the arrangement looks like for the specific account before accepting. Honest fit guidance: the deciding question is not technical, it is temperamental. If you like building a deep relationship with one customer's environment, knowing its history and its quirks, and being the person they call, this is unusually satisfying work. If you would find that confining, the escalation or Center of Excellence roles at the same company suit better and are also on this board. Eight years of genuinely customer facing technical work is the bar, so pure internal engineering experience will not map cleanly.
What the posting requires: - 8 to 10 or more years of experience in solutions architecture, technical consulting or enterprise SaaS implementations. What this kind of role typically involves at an enterprise SaaS company, based on how the posting frames it: - Owning the technical relationship with customers through implementation and adoption. - Designing how the platform integrates with the customer's existing systems and processes. - Translating business requirements into a technical configuration and integration approach. - Working alongside sales, customer success and product teams. ⚠️ The geography matters here. NAMER in the title means the accounts are North American while the role is based in Pune, so working hours are likely to be shifted to overlap with North American time zones. Confirm the expected shift pattern early in the process, because it is the single largest lifestyle factor in this role and the posting does not spell it out. About the employer: Mindtickle is a revenue enablement platform used by sales organisations for onboarding, training, coaching and readiness. Its engineering and delivery presence in India is in Pune, where it also lists other technical roles. Location and working pattern: Pune, Maharashtra. Office days are not stated in the posting. Honest fit guidance: this is a customer facing technical role, so the skills being bought are as much communication and structured thinking as they are technical depth. If you have implemented enterprise SaaS for large customers and can hold a room of stakeholders through a design decision, the 8 year bar is a fair reflection of the seniority. If you want to write product code, this is not that job. Because the posting is light on a detailed requirements list, ask for specifics on the tech stack, the size of accounts, and the split between pre-sales and post-sales work before investing in the process.
What the posting requires: - 9+ years of relevant experience with a Bachelor's or Master's degree in Computer Science or Electrical Engineering, or 6+ years with a PhD. The posting states this tradeoff explicitly, which is unusual and worth noting if you hold a doctorate. - Extensive experience designing, building and operating distributed data platforms at large scale, with Spark, Kafka and Flink named. - Proficiency in Java, Scala or Python, along with strong data processing and SQL querying skills. - A proven track record of designing and optimising both batch and real time data pipelines. - Strong collaboration skills, with the ability to work with product managers, data scientists and engineers. - Advanced problem solving and analytical skills. What the work actually looks like: - Design, build and operate the distributed data platforms that Airbnb's internal business technology runs on. - Build and optimise batch and real time pipelines feeding analytics and operational systems. - Partner with product managers, data scientists and engineers across the BizTech organisation. About the team: BizTech provides reliable corporate tools, products and technical support for teams across Airbnb, and describes its purpose as driving technical breakthroughs that deliver value for the business and its people. It is internal platform work rather than guest or host facing product. Location and working pattern: Bangalore, India. This is the Bangalore based role. Airbnb does list some genuinely remote India positions in other teams, but this posting is location based, so do not assume remote. Honest fit guidance: the PhD clause is the detail most people will skim past, and it materially changes who should apply. At 9 years without one, or 6 with one, this is a senior individual contributor data engineering role at a company whose data volumes are genuinely large. The named technologies are conventional for the discipline, so the differentiator in an application will be evidence of having operated these platforms in production rather than only built on top of them.
What the posting requires: - 10+ years of experience working on software and operating distributed systems, with deep Kubernetes expertise including designing or evolving multi cluster platforms. - Proficiency in Python, Go or a similar programming language. - Understanding of workload isolation at the systems level: containers, virtual machines, and the tradeoffs between them for running untrusted code. - A customer focused mindset. - Valuing efficiency in processes and operations, with a strong preference for automation over manual processes. What the posting sets as position expectations: - Own the reliability architecture of the platform across regions and cloud providers. - Collaborate with the teams building the platform, providing internal support and guidance on operability, capacity and best practices. - Set operational standards for the team: on call quality, incident response and service level objective discipline. - Mentor and technically develop the SRE team. - Participate in a 24 by 7 on call rotation to resolve issues involving platform infrastructure. ⚠️ The on call commitment is stated plainly as a 24 by 7 rotation. At staff level that usually means you are also the escalation point for others' incidents. Weigh it honestly against the seniority and scope on offer. The detail worth noticing: the requirement about running untrusted code tells you something about the platform. Isolation tradeoffs between containers and virtual machines only become a live question when you are executing code you did not write, which makes this a more interesting systems problem than standard service reliability work. Location and working pattern: the posting states MongoDB is looking for candidates based in Bengaluru for its hybrid working model. Honest fit guidance: ten years plus deep multi cluster Kubernetes is a high and specific bar. The distinguishing experience is having designed or evolved multi cluster platforms rather than operated a single one, and being able to talk about isolation tradeoffs concretely. If you have that, the scope here, reliability architecture across regions and clouds, is genuinely staff level rather than a retitled senior role.
What the posting requires: - 10+ years of overall industry experience, with 6+ years shipping and sustaining production C++ (C++11 and later, including 14, 17 and 20): multi threaded, memory conscious, cross platform code. - Solid distributed systems fundamentals: routing, failover, backpressure, graceful degradation, and the failure modes that come with them. - Deep experience building and sustaining endpoint, client or systems software. - Expertise with data structures, algorithms and performance profiling. - Fluency with agentic coding systems and genuine curiosity about agent harnesses. - A BSCS or equivalent is required, with MSCS or equivalent preferred. What the work actually looks like: - Build and harden the C++ client runtime at the core of the product: lightweight, multi threaded, cross platform, macOS first then Windows. - Architect the distributed systems that keep it fast and resilient at scale, engineering for fault tolerance so failures degrade gracefully rather than breaking a session. - Build a secure agentic harness for safe, high performance execution. - Own reliability, observability, security and performance of the runtime across real, varied hardware. - Set patterns and standards for the endpoint codebase. Why this is a harder problem than it sounds: an endpoint agent runs on hardware you do not control, alongside software you did not choose, and it cannot fail loudly without breaking someone's working day. The posting's emphasis on graceful degradation and varied real hardware is the honest description of that constraint. Levelling: the title spans Staff and Senior Staff, and Netskope's postings state that teams hire across levels with candidates individually assessed and levelled on skills and experience. Location and working pattern: Bengaluru. Netskope describes open desk office layouts, so expect an in office team. Office days are not stated. Honest fit guidance: the 6 years of production C++ is the filter, and it means shipped and sustained rather than studied. Modern C++ across macOS and Windows with real multi threading is a narrower skill than a general backend background, and people who have it are in demand. If that is you, this is one of the more technically serious roles on today's board.
What the posting requires as minimum: - 10+ years of engineering experience, with 5+ years of hands on experience building and operating data systems and pipelines, datasets and data warehouses, infrastructure, and leading small teams to deliver solutions. - A strong engineering background and a genuine interest in data. - Prior experience writing and debugging data pipelines using a distributed data framework such as Spark, Hadoop or Trino. - An inquisitive nature, diving into data inconsistencies to pinpoint issues and resolve deep rooted data problems. Stripe states that the preferred qualifications are a bonus rather than a requirement, and that if you meet the minimum requirements you are encouraged to apply. What the work actually looks like: - Lead the technical outcomes for a team of engineers working on high impact, cutting edge data problems. - Build and operate data pipelines at large scale using the modern data engineering toolchain: Airflow, Spark, Kafka and Flink are named in the posting. - Collaborate with other Stripe teams to understand their use cases and unlock new capabilities for them. - Build strong working relationships across the company, which the posting treats as a core requirement rather than a soft extra. What the emphasis on empathy tells you: for a staff role at this scale, most of the hard problems are cross team. The posting naming empathy and relationship building alongside Spark and Kafka is a signal about how the role is actually evaluated. Location and working pattern: Bengaluru, India. Office days are not stated in the posting. Honest fit guidance: ten years is a real bar and the 5 years of hands on data systems work is the substantive part. The phrase leading small teams appears in the minimum requirements, so this is a technical leadership role even though it is an individual contributor title. If your data engineering has been solo or within one team, the cross organisation scope is the stretch. If you have led data platform work that other teams depended on, that is exactly the story to tell.
What the posting requires: - 10+ years of overall software and integration engineering experience, with 8+ years focused on API and enterprise integration. - 4+ years in a senior, lead or architect capacity, owning API and integration designs, patterns and technical decisions. What the work actually looks like: API and integration architecture: - Own the API and integration architecture and strategy for assigned domains, defining API led patterns across experience, process and system APIs, plus reference architectures and standards. - Design, build and evolve RESTful APIs with clear contracts, documentation and service level agreements for internal and external consumers. - Lead integrations between SaaS and on premises applications including NetSuite, Workday, Salesforce, Snowflake and ServiceNow. - Define non functional requirements and SLAs for APIs and integrations covering availability, latency, throughput, error budgets, RTO and RPO. - Drive observability and reliability by standardising logging, tracing, metrics, dashboards and alerting, and creating operational runbooks for incident response and post incident reviews. AI and intelligent automation: - Identify and prioritise AI opportunities within API and integration flows such as data enrichment, anomaly detection, routing, summarisation, classification and intent extraction. - Define safe and governed AI usage: clear input and output contracts for AI services, guardrails through prompt design, validation and constraints, handling of sensitive personal, financial and HR data in prompts and responses, and monitoring for model performance and drift in production. Governance and delivery: - Partner with security, compliance and audit teams so integrations, APIs and AI services meet security, privacy and regulatory requirements including SOX sensitive data flows, access control, encryption and audit trails. - Lead technical discovery and solution design for new initiatives with product managers, application owners and business stakeholders. - Own vendor and platform technical relationships, anticipating deprecations and coordinating upgrades and migrations. - Oversee CI/CD practice including branching and release strategy, automated testing and environment configuration across development, QA, UAT and production. ⚠️ Applying to Rubrik: rubrik.com returns 403 to automated requests, so this listing was verified live through the Greenhouse jobs API rather than by fetching the page. It opens normally in a browser. Location and working pattern: Bangalore, India. Office days are not stated. Honest fit guidance: the AI governance section is the part that will separate applications, because plenty of engineers have integration depth and far fewer have put guardrails around AI in a SOX sensitive flow.
What the posting requires: - A Bachelor's or Master's degree in Computer Science, Engineering, Information Systems or a related field. - 10 to 15+ years in data engineering or platform architecture, with a shift toward high level technical leadership. - Strong experience designing and implementing modern data architectures and cloud data platforms. - Deep hands on expertise in full stack development including frontend and backend technologies, and DevOps infrastructure. - Experience with Snowflake, Tableau or similar technologies. - Expertise in AI and ML platforms, and the engineering required to support generative AI at scale. What the work involves, based on how the posting frames the role: architecture ownership across Rubrik's AI data platform, meaning the design of the data foundations and the platform engineering that generative AI capabilities are built on, rather than building individual features. The breadth requirement covering frontend, backend and DevOps suggests the architecture spans a full product surface rather than one layer. What kind of role this is: an architect title with an explicit expectation of high level technical leadership means influence, standards and direction setting, with hands on credibility as the entry ticket. If you want to be writing production code most days, an architect seat at this level is usually not that, and the posting is honest about the shift it expects. ⚠️ Applying to Rubrik: rubrik.com returns 403 to automated requests, so this listing was verified live through the Greenhouse jobs API rather than by fetching the page directly. It opens normally in a browser. About the employer: Rubrik builds data security and cyber resilience software for enterprises, protecting and recovering data across cloud, SaaS and on premises environments. Location and working pattern: Bengaluru, India. Office days are not stated in the posting. Honest fit guidance: the breadth is the thing to be honest with yourself about. Data platform architecture plus full stack plus DevOps plus generative AI at scale is a lot of surface, and few people are genuinely deep in all of it. Treat the data architecture and AI platform experience as the core, and the rest as areas where working knowledge and good judgement will do. If your background is purely data warehousing without the AI platform side, that is the gap the posting cares about most.
What the posting states: - Successful candidates for this position typically have 10 to 15 years of experience in a customer or partner facing technical role. The posting frames this as typical rather than an absolute cut off, which is worth knowing if you are close to the range. - A self starter, technically capable professional comfortable operating with autonomy. What this kind of role involves, based on how the posting frames it: enabling global system integrator partners in India to build practices around Datadog, which typically covers technical enablement of partner engineers, supporting partner led solution design, building reference material and demonstrations that partners can reuse, and acting as the technical bridge between the partner organisation and Datadog's own teams. Why the GSI focus changes the job: working through system integrators is different from selling to a customer directly. Your leverage comes from making other organisations capable rather than from personally delivering, so the skills that matter most are teaching, structuring reusable material, and building trust inside a partner's delivery practice. Prior experience working with or inside a system integrator is the most relevant background you can bring. About the product context: Datadog's platform covers infrastructure monitoring, application performance monitoring, log management and security monitoring, so technical credibility here means being able to hold a conversation about how an engineering organisation actually observes and debugs its systems. Location and working pattern: Bangalore, India. Office days are not stated in the posting. Honest fit guidance: at 10 to 15 years this is a senior seat, and the partner lens is the differentiator rather than the product knowledge, which can be learned. If your experience is solutions architecture for direct customers only, the partner motion, co-sell, practice building and enablement, is a genuinely different muscle and worth addressing directly in your application. Because the posting is light on a detailed responsibilities list, ask early about which partners you would cover and how success is measured, since partner roles vary widely on that.
What the posting requires: - 10+ years of successful experience in customer facing technical sales or consulting roles focused on enterprise database technologies and cloud. - A Bachelor's degree in Computer Science, Engineering, or equivalent experience. Core expertise, with deep technical proficiency required in: - Microsoft SQL Server: architecting and managing large scale high availability and disaster recovery solutions, including extensive experience with Always On Availability Groups, Failover Cluster Instances and log shipping. - Cloud databases: design and management of Azure SQL and Azure SQL Managed Instance. What this kind of role involves: acting as the deep database specialist in customer engagements, designing how enterprise SQL Server estates are protected and recovered, and advising customers on architecture decisions that carry real consequences if a recovery is ever needed. Rubrik's product is data security and cyber resilience, so the conversations are about backup, recovery, ransomware resilience and business continuity for databases that organisations cannot afford to lose. Why the specialism is worth noting: HADR architecture for SQL Server at enterprise scale is a genuinely narrow skill. Most database professionals administer, fewer architect availability groups and failover clusters, and fewer still can do that while sitting in front of a customer explaining the tradeoffs. If you are in that overlap, roles like this are where that combination is valued most. ⚠️ Applying to Rubrik: rubrik.com returns 403 to automated requests, so this listing was verified live through the Greenhouse jobs API rather than by fetching the page directly. It opens normally in a browser. Location and working pattern: Bengaluru, India. Office days are not stated in the posting. Honest fit guidance: read the customer facing technical sales or consulting phrasing carefully. This is a pre-sales and consulting seat, so commercial outcomes are part of how it is judged, and the technical depth is what earns the right to be in the room. If you are a SQL Server DBA who enjoys the customer facing side, this is a natural next step. If you want to stay purely hands on inside one estate, it is not.
What the posting requires: - 12+ years of production level experience in one of Python, Java, Scala, C++ or a similar language. - Experience developing large scale distributed systems from scratch. - Hands on experience developing and operating backend systems. - The ability to contribute effectively throughout all project phases, from initial design and development through implementation and ongoing operations. What the work actually looks like at this level, based on how Databricks describes its staff engineering: - Deliver highly scalable, available and fault tolerant systems processing very large data volumes across thousands of customers. - Low level systems debugging, performance measurement and optimisation on large production clusters. - Build architecture designs, influence the product roadmap, and take ownership of new projects. - Help prevent and investigate production issues. - Plan and lead complex technical projects spanning several teams within the company. - Break complex problems quickly into potential solutions, knowns and unknowns, and de risk them through prototyping and validation. The scale you would be working at, in the company's own terms: millions of virtual machines, terabytes of logs and exabytes of data processed daily, with hardware, network and operating system faults treated as expected conditions rather than emergencies. Location and working pattern: Bengaluru. Databricks says it is in the process of setting up new teams from scratch at this site, so expect an in office or hybrid arrangement. The number of days is not stated in the posting. Compliance note in the posting: the standard Databricks export controlled technology clause applies. Where access to export controlled technology or source code is required, applying for a US government licence is at the employer's discretion, and it may decline to proceed with an applicant on that basis alone. Honest fit guidance: twelve years is the real bar and it is the highest on this edition. What distinguishes an application at this level is not more of the same experience but evidence of having led complex, multi team technical projects and having made architectural calls that survived contact with production. If you are at eight to ten years, Databricks has several roles on this board at that level, and stretching for this one is unlikely to clear the filter.