Forward Deployed Engineer at Databricks
San Francisco, CA · 30+ FDEs · $175,000 - $260,000
Overview
Databricks FDEs deploy the Databricks Lakehouse Platform and Mosaic AI tools inside enterprise data teams. As one of the highest-valued private tech companies, Databricks' FDE equity could be worth significantly more than the base salary if the company goes public. FDEs at Databricks sit at the intersection of data engineering, ML/AI, and customer deployment, making it one of the most technically demanding FDE roles in the market.
What FDEs Do at Databricks
Databricks FDEs build custom data pipelines, ML workflows, and AI applications on the Databricks platform for enterprise customers. Typical projects: migrating a customer's data warehouse to a lakehouse architecture, building MLOps pipelines for model training and deployment, implementing Unity Catalog for data governance across a customer's organization, and deploying Mosaic AI for custom model fine-tuning. The role is heavier on data engineering than most FDE positions. FDEs work with Apache Spark, Delta Lake, MLflow, and Databricks' proprietary tools daily.
Tech Stack
Python, SQL, Apache Spark, Delta Lake, MLflow, Databricks Notebooks, Unity Catalog, Mosaic AI, Terraform, Docker, AWS/Azure/GCP. Strong data engineering fundamentals are essential. FDEs who understand distributed computing, data modeling, and ML pipelines thrive. Web development skills are less important than at other FDE roles.
Interview Process
Databricks FDE interviews are 4-5 rounds: recruiter screen, coding (data-focused Python, SQL heavy), system design (expect a data pipeline or lakehouse architecture question), customer scenario, and a team/values round. The technical bar is high. Databricks wants engineers who can explain complex data concepts to non-technical stakeholders. Strong SQL skills are surprisingly important for this role.
Culture & Work-Life
Engineering-centric culture with a strong open-source heritage (Apache Spark originated at Databricks). FDEs are treated as peers to product engineers, not as a separate support organization. The company is growing fast with pre-IPO energy. Compensation is competitive, and the equity component could be substantial. Travel is moderate (20-30%). Remote-friendly for many FDE roles.
Frequently Asked Questions
What is the Databricks FDE salary and equity?
Base salary ranges from $175,000 to $260,000. Total compensation including RSUs (restricted stock units) can reach $350,000-$450,000 at senior levels. As a private company valued at $43B+, Databricks equity isn't liquid yet but could be very valuable at IPO. FDEs who join pre-IPO with significant equity grants stand to benefit most.
Do I need Spark experience to be a Databricks FDE?
It's strongly preferred but not strictly required. If you have strong Python, SQL, and general data engineering experience, you can learn Spark on the job. However, candidates who already know Spark, Delta Lake, and the Databricks platform have a significant advantage in interviews and ramp up to customer deployments much faster. Consider getting a Databricks certification before applying.
How technical is the Databricks FDE role?
Very technical. Databricks FDE is one of the most engineering-heavy FDE roles in the market. You'll write production data pipelines, optimize Spark jobs, build ML workflows, and debug distributed computing issues. If you're looking for an FDE role that's closer to data engineering than customer management, Databricks is the right fit.
Is Databricks FDE a good path to ML engineering?
Excellent. Databricks FDEs work daily with ML tooling (MLflow, Mosaic AI, model deployment pipelines). The customer exposure gives you applied ML experience that pure ML engineers in research labs don't get. Many Databricks FDEs transition to ML engineering or MLOps roles, either within Databricks or at other companies.
Does Databricks have FDE roles outside San Francisco?
Yes. Databricks has FDE roles in multiple locations including New York, Seattle, London, and some remote positions. The company is more distributed than OpenAI or Anthropic. Remote FDE roles require periodic customer site visits but are available for candidates who prefer not to relocate to the Bay Area.
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