Sr. Forward Deployed Engineer (FDE) - Digital Native Business
Not focused on vibe coding — this is production-grade data+AI engineering (Spark, MLOps, cloud) working with customers and models in production.
About the Role
The Senior Forward Deployed Engineer partners with customers to design, build, and productionize end-to-end data and AI solutions on the Databricks platform, owning architecture and delivery. This customer-facing role combines hands-on engineering across data engineering, ML/AI, and application development with stakeholder engagement and measurable technical impact.
Job Description
Role
As a Senior Forward Deployed Engineer (FDE), you will work directly with customers to build and productionize solutions to data and AI challenges using the Databricks platform. You will own architecture and design decisions and implement end-to-end systems spanning data engineering, ML/AI, and application development while collaborating with engineering, product, and customer teams.
Key Responsibilities
- Deliver production-grade systems, reference architectures, custom applications, data ingestion pipelines, and ML/AI integrations for customers.
- Lead architecture and design decisions, ensuring solutions are secure, scalable, and align with Databricks best practices.
- Guide strategic customers through end-to-end design, build, and deployment of big data and AI applications.
- Embed with customer teams across technical ICs to executives to deeply understand challenges and deliver impact.
- Work cross-functionally with engagement managers, project managers, architects, engineering, and customer support to scope and deliver engagements.
- Contribute reusable accelerators, frameworks, and best practices to scale impact across accounts and influence the product roadmap.
Requirements
- 6+ years of experience in data engineering, data platforms & analytics, or software engineering.
- Comfortable writing code in Python, Scala, JavaScript/TypeScript and using modern frameworks.
- Working knowledge of two or more cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
- Deep experience with distributed computing and Apache Spark, including knowledge of Spark runtime internals.
- Familiarity with CI/CD for production deployments and working knowledge of MLOps, ML/AI models and AI APIs.
- Experience designing and deploying performant production end-to-end data architectures combining pipelines, models, and user-facing interfaces.
- Experience with technical project delivery: managing scope, timelines and measurable outcomes.
- Strong documentation and white-boarding skills, customer empathy, and experience working with enterprise clients and broad stakeholders.
- Willingness to travel to customers (~20% travel) and be based in or spend significant time in the San Francisco Bay Area (see Location).
- Databricks Certification (listed as a requirement).
Location & Travel
This role is San Francisco Bay Area–focused. Candidates should be based in the Bay Area, willing to relocate, or able to travel to the area at least one week per month to spend meaningful time with customers and the team. Expected customer travel is approximately 20%.
Compensation & Benefits
- Local base pay range listed: $182,000 — $250,208 USD.
- Total compensation may include annual performance bonus, equity, and region-specific benefits. For full details on benefits by region, the posting links to the company benefits documentation.