Staff Forward Deployed Engineer

Databricks · Remote - India · Professional Services Operations · listed July 8, 2026

The shape of it

Seniority
Staff
Experience asked
2–15 years
Where
Remote
Requirements listed
11
Length
639 words

In the posting’s own words

As a Staff FDE in our Professional Services team, you will partner with a diverse range of customers to tackle their big data challenges using the Databricks Platform. In this customer-focused role, you will act as a trusted advisor, delivering tailored solutions in data engineering and data science across multiple cloud environments, ensuring successful outcomes for our clients. You come with a strong product development mindset and deliver robust and scalable automation utilities that can be adopted by multiple customers across the domains. You bring in a strong AI focused problem solving skills yet secure and proven guardrails that can be leveraged by the customers across different sectors.

What it asks for · 11

  • 15+ years experience with Big Data Technologies such as Apache Spark™, Kafka, Cloud Native and Data Lakes in a customer-facing post-sales, technical architecture or consulting role
  • 6+ years of experience working on Big Data Architectures independently
  • 2+ years of experience working on AI based implementations including RAG, MCP, Context engineering etc .
  • Strong experience working in the Databricks ecosystem
  • Comfortable writing code in either Python or Scala .
  • Experience working across Cloud Platforms ( GCP / AWS / Azure )
  • Documentation and white-boarding skills.
  • Excellent problem solving and critical thinking skills that turn business problems in to reliable technical products
  • Build skills in technical areas that support the deployment and integration of Databricks-based solutions to complete customer projects.
  • Excellent stakeholder management skills to collaborate with both technical and domain experts
  • Highly customer-obsessed, innovative and think beyond the current world and come up with innovative solutions that can last long in the GenAI world

What the job covers

  • Collaborate on impactful customer big data projects, such as creating reference architectures, developing how-to guides, and building production-ready efficient, robust and scalable tools and technologies.
  • Advise strategic customers on transformational big data initiatives, including third-party migrations and the complete design, build, and deployment of cutting-edge big data and AI applications.
  • Provide expertise in architecture and design, and support key customer projects to ensure successful adoption and integration of Databricks solutions.
  • Partner with Engineering and Customer Support teams to deliver feedback, resolve engagement-specific issues, and drive continuous product improvements.
  • Simultaneously manage and guide multiple diverse projects, ensuring adherence to well-architected principles and quality standards, proactively identifying and mitigating risks, and building strong customer trust.

Tools and skills named

Data
  • Databricks4×
  • Spark2×
Cloud & infra
  • AWS
  • Azure
  • GCP
  • Kafka
Languages
  • Python
  • Scala
Operations & finance
  • Stakeholder management
Ways of working
  • Technical writing

Words the posting leans on

  • customer9×
  • big data6×
  • experience5×
  • skills5×
  • architecture4×
  • projects4×
  • solutions4×
  • technical4×
  • cloud3×
  • engineering3×
  • multiple3×
  • product3×
  • support3×
  • build2×
  • building2×
  • collaborate2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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How this page was made

An automated read of a public job posting, fetched August 24, 2026 and last changed by Databricks on August 18, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.