Senior forward deployed engineer (L5) at Databricks, remote from India, building and productionizing data and AI solutions directly with customers.

This remote (India) full-time role was posted on 19 October 2026. The listing describes working with customers to build and productionize solutions to their data and AI challenges on the Databricks platform, owning architecture, leading design decisions and implementing end-to-end systems spanning data engineering, AI and application development. FDEs also work cross-functionally with engineering, product and developer relations to shape strategic priorities. Requirements include 9+ years in data engineering, data platforms and analytics, or software engineering, and comfort writing code in Python, Scala, JavaScript/TypeScript and modern frameworks.

About Databricks

Databricks builds a data and AI platform around the lakehouse architecture, combining data warehousing and data lakes for analytics, data engineering and machine learning. The company was founded by the creators of Apache Spark.

Databricks has a large engineering presence in Bengaluru, with listings spanning platform engineering, monitoring and reliability, and customer-facing engineering roles. Learn more on Databricks's website.

The role in plain terms

The FDE model differs from both consulting and product engineering: you embed with customers to ship production systems, then feed what you learn back into product priorities - the listing names that loop explicitly. The 9+ year bar and architecture ownership make this a senior hands-on seat, not an advisory role. The remote-India location with customer-facing delivery means communication discipline matters as much as code.

The team and the work

Per the listing, the work spans data engineering, AI and application development on the Databricks platform, for strategic customers implementing large data projects. The polyglot code requirement (Python, Scala, TypeScript) reflects the variety of customer environments.

What the employer asks for

These requirements are quoted from the employer's listing, kept in their exact words so eligibility details are not distorted:

9+ years of experience in data engineering, data platforms & analytics, or software engineering
Comfortable writing code in either Python, Scala, JavaScript/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 with Apache Spark™ and knowledge of Spark runtime internals
Familiarity with CI/CD for production deployments
Working knowledge of MLOps, ML/AI models and AI APIs
Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.

Who this role suits

Senior data or software engineers with 9+ years who like customer-facing delivery and can own architecture end to end. Strong fit for consultants who want to build rather than advise. Not for engineers who prefer internal product work away from customers.

Practical notes

For FDE roles, expect a technical deep-dive on a production system you delivered for a customer or stakeholder, plus scenario questions on handling ambiguous requirements. Comfort presenting to customer engineers is typically assessed.

Working at Databricks

Work at Databricks centres on large-scale data systems: query engines, orchestration, observability and the infrastructure that runs customer data and AI workloads.

How to apply

Apply directly on the employer's site: Senior Forward Deployed Engineer, Sr FDE (L5) at Databricks. We found this listing on the Greenhouse public job board (databricks.com), where it was posted on 19 Oct 2026 and was still open when we checked on 30 Oct 2026. Before applying, re-read the employer's own description in full, since eligibility details, deadlines and process steps can change at any time and the employer's page is always the final word. Tailor your resume to the specific requirements above rather than sending a generic one: mirror the skills and tools the listing names where you genuinely have them. A short, specific note on why this team and this problem interest you goes further than a long generic cover letter. Never pay a fee to apply or interview; genuine employers, including this one, do not charge candidates.

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