Databricks
About this role
Databricks builds the data and AI platform used by more than 10,000 organisations, and this role is in Professional Services, so you would work inside customer environments rather than on the product. A Forward Deployed Engineer is a hands on consultant: designing reference architectures, running third party migrations onto Databricks, and building automation utilities reusable across multiple clients. Databricks specifically wants a product development mindset here, meaning it expects tools other customers can adopt rather than one off scripts. The current emphasis is AI implementation work including RAG, MCP and context engineering, with guardrails customers can trust. The stack is Apache Spark, Kafka, data lakes and cloud native services across AWS, GCP and Azure, with Python or Scala. It is remote within India.
Who this is for
What the posting asks for:
- 15+ years with big data technologies such as Apache Spark, Kafka, cloud native services and data lakes, in a customer facing post sales, technical architecture or consulting role.
- 6+ years working on big data architectures independently.
- 2+ years on AI based implementations including RAG, MCP and context engineering.
- Strong experience within the Databricks ecosystem.
- Comfortable writing code in either Python or Scala.
- Experience across cloud platforms: GCP, AWS or Azure.
- Documentation and whiteboarding skills.
- Excellent problem solving and critical thinking, turning business problems into reliable technical products.
- Strong stakeholder management, working with both technical people and domain experts.
The day to day: collaborating on customer big data projects, creating reference architectures and how to guides, building production ready tooling, advising strategic customers on transformational initiatives including third party migrations, providing architecture and design expertise, partnering with Engineering and Customer Support to feed issues back into the product, and running several diverse client projects at once while managing risk and building trust.
Experience: the posting states 15+ years as the headline requirement. Read the three numbers as a stack rather than alternatives: 15+ years overall in a customer facing big data role, 6+ years on big data architectures independently, and 2+ years specifically on AI implementations. The AI requirement is the newest and probably the one most people will fail, not the 15.
Location: remote within India. This is one of very few remote senior data roles on the board today.
Who should apply: a senior data architect or consultant who genuinely likes customer facing delivery. If you want to build product rather than deliver projects, this is the wrong side of Databricks. Note also that the AI expectation is concrete, not decorative: they want RAG and MCP work you have actually shipped.
- 15+ years with big data technologies such as Apache Spark, Kafka, cloud native services and data lakes, in a customer facing post sales, technical architecture or consulting role.
- 6+ years working on big data architectures independently.
- 2+ years on AI based implementations including RAG, MCP and context engineering.
- Strong experience within the Databricks ecosystem.
- Comfortable writing code in either Python or Scala.
- Experience across cloud platforms: GCP, AWS or Azure.
- Documentation and whiteboarding skills.
- Excellent problem solving and critical thinking, turning business problems into reliable technical products.
- Strong stakeholder management, working with both technical people and domain experts.
The day to day: collaborating on customer big data projects, creating reference architectures and how to guides, building production ready tooling, advising strategic customers on transformational initiatives including third party migrations, providing architecture and design expertise, partnering with Engineering and Customer Support to feed issues back into the product, and running several diverse client projects at once while managing risk and building trust.
Experience: the posting states 15+ years as the headline requirement. Read the three numbers as a stack rather than alternatives: 15+ years overall in a customer facing big data role, 6+ years on big data architectures independently, and 2+ years specifically on AI implementations. The AI requirement is the newest and probably the one most people will fail, not the 15.
Location: remote within India. This is one of very few remote senior data roles on the board today.
Who should apply: a senior data architect or consultant who genuinely likes customer facing delivery. If you want to build product rather than deliver projects, this is the wrong side of Databricks. Note also that the AI expectation is concrete, not decorative: they want RAG and MCP work you have actually shipped.
Apply on company site
Opens job-boards.greenhouse.io, the employer's own application page. Applying is always free.