Databricks
About this role
Forward Deployed Engineers at Databricks work directly with customers to build and productionise solutions to their data and AI problems on the Databricks platform. You would own the architecture, lead design decisions and implement end to end systems spanning data engineering, AI and application development, then integrate with client systems and train their teams. The posting is honest that this is billable delivery work: FDEs are described as billable and expected to complete projects to specification with strong customer empathy. Beyond delivery there is a product feedback loop, since you contribute accelerators, frameworks and best practices that scale across accounts and influence the roadmap, and you work with Databricks engineering and support to resolve engagement specific product issues. Travel to customers is stated at about 20 percent of the time, and a Databricks certification is listed among what they look for.
Who this is for
What the posting requires:
- 6+ years of experience in data engineering, data platforms and analytics, or software engineering.
- Comfort writing code in Python, Scala or JavaScript and TypeScript, and modern frameworks.
- Working knowledge of two or more common cloud ecosystems (AWS, Azure, GCP), with expertise in at least one.
- Deep experience with distributed computing using Apache Spark, including knowledge of Spark runtime internals.
- Familiarity with CI/CD for production deployments.
- Working knowledge of MLOps, ML and AI models, and AI APIs.
- Experience designing and deploying performant production data architectures and applications combining data pipelines, ML and AI models, and user facing interfaces.
- Experience with technical project delivery: managing scope, timelines and measurable outcomes.
- Documentation and whiteboarding skills.
- Experience working with enterprise clients and managing conflict across a broad stakeholder range.
- Willingness to travel to customers about 20 percent of the time.
- A Databricks certification.
What the work actually looks like:
- Lead customer technical projects, delivering production grade systems, reference architectures, custom applications, and data ingestion with ML and AI model integration.
- Guide strategic customers through transformational big data projects, from end to end design through build and deployment.
- Work with engagement managers to scope technical delivery with customer input.
- Own architecture and design decisions, keeping solutions secure, scalable and aligned to both customer needs and Databricks best practice.
- Embed with customer teams, engaging with stakeholders from individual contributors to executives.
- Work with Databricks engineering and customer support to feed back product and implementation issues and drive rapid resolution.
- Contribute accelerators, frameworks and best practices that scale across accounts and influence the product roadmap.
Location and working pattern: Bengaluru, with roughly 20 percent travel to customers.
Compliance note in the posting: the standard Databricks export controlled technology clause applies.
Honest fit guidance: this is a hands on customer facing engineering role, not a solutions architect who only advises. The posting says it is for builders who thrive at the intersection of technology and business impact, and the billable framing is worth taking seriously: delivery to specification and to date is how the work is judged.
- 6+ years of experience in data engineering, data platforms and analytics, or software engineering.
- Comfort writing code in Python, Scala or JavaScript and TypeScript, and modern frameworks.
- Working knowledge of two or more common cloud ecosystems (AWS, Azure, GCP), with expertise in at least one.
- Deep experience with distributed computing using Apache Spark, including knowledge of Spark runtime internals.
- Familiarity with CI/CD for production deployments.
- Working knowledge of MLOps, ML and AI models, and AI APIs.
- Experience designing and deploying performant production data architectures and applications combining data pipelines, ML and AI models, and user facing interfaces.
- Experience with technical project delivery: managing scope, timelines and measurable outcomes.
- Documentation and whiteboarding skills.
- Experience working with enterprise clients and managing conflict across a broad stakeholder range.
- Willingness to travel to customers about 20 percent of the time.
- A Databricks certification.
What the work actually looks like:
- Lead customer technical projects, delivering production grade systems, reference architectures, custom applications, and data ingestion with ML and AI model integration.
- Guide strategic customers through transformational big data projects, from end to end design through build and deployment.
- Work with engagement managers to scope technical delivery with customer input.
- Own architecture and design decisions, keeping solutions secure, scalable and aligned to both customer needs and Databricks best practice.
- Embed with customer teams, engaging with stakeholders from individual contributors to executives.
- Work with Databricks engineering and customer support to feed back product and implementation issues and drive rapid resolution.
- Contribute accelerators, frameworks and best practices that scale across accounts and influence the product roadmap.
Location and working pattern: Bengaluru, with roughly 20 percent travel to customers.
Compliance note in the posting: the standard Databricks export controlled technology clause applies.
Honest fit guidance: this is a hands on customer facing engineering role, not a solutions architect who only advises. The posting says it is for builders who thrive at the intersection of technology and business impact, and the billable framing is worth taking seriously: delivery to specification and to date is how the work is judged.
Apply on company site
Opens databricks.com, the employer's own application page. Applying is always free.