Sr. Forward Deployed Engineer - National Security

About the Role

As a Sr. Forward Deployed Engineer (FDE), you will work with federal government customers to build and productionize 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.

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

*Note: This role is hybrid and requires travel to customer locations 20-25% of the time.*

Clearance Requirement

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.

Impact & Responsibilities

• Production Solution Delivery: Lead customer technical projects by delivering production-grade systems, designing reference architectures, custom applications, and data ingestion/ML/AI model integration.
• Transformational Impact: Guide strategic customers through big data and AI implementations, working with engagement managers to scope technical delivery.
• Empower Customers: Guide customers on architecture and design to accelerate evaluation and adoption of Databricks.
• Own the Architecture: Lead architecture and design decisions ensuring solutions are secure, scalable, and aligned with best practices.
• Deliver Technical Components: Partner with technical teams, project managers, and architects to fulfill engagement goals.
• Cross-Collaborate: Interface with engineering and support teams to provide product feedback and resolve issues.
• Customer Immersion: Embed directly with customer teams, from technical ICs to executive stakeholders.
• Reusable Assets: Contribute accelerators, frameworks, and best practices that scale impact across accounts.

Qualifications

Minimum Qualifications

• 6+ years of experience in data engineering, data platforms & analytics, or software engineering
• Fluency in writing code in 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
• Experience designing and deploying performant production end-to-end data architectures combining data pipelines, ML/AI models, and user-facing interfaces
• Experience with technical project delivery, documentation, white-boarding, and managing conflicts across diverse stakeholders

Preferred Qualifications

• Expertise in MLOps, ML/AI models, and AI APIs
• Databricks Certification