Forward Deployed Engineer; FDE; Public Sector
Listed on 2026-10-15
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Software Development
AI Engineer (Applied/Software), Data Engineering
CSQ
327R219PL
EASE NOTE
:
Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply.
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines.
And we're only getting started.
As a Sr. Forward Deployed Engineer (FDE), you will work with federal government customers to build and product ionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations.
FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes.
FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.
Please note:
this role is hybrid and has a requirement to travel to customer locations 20-25% of the time.
Production Solution Delivery
Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
Transformational ImpactGuide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
Empower CustomersGuide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks
Own the ArchitectureLead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices
Deliver Technical ComponentsWork with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs
Cross-CollaborateWork with Engineers and Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues
Customer ImmersionEmbed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact
Reusable Assets & ScaleContribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap
What We’re Looking For:Minimum Qualifications:
- 5+ years experience in data engineering, data platforms & analytics, or software engineering
- Fluency in writing code in Python, Scala, JavaScript/Type Script, 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, documentation and…
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