Sr. Forward Deployed Engineer (FDE) - Public Sector/National Security

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.

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.

Responsibilities:

• 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 Impact: Guide 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.
• Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customer's successful understanding, evaluation, and adoption of Databricks.
• Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
• Deliver Technical Components: Work with the Databricks technical team, Project Manager, Architect, and Customer team to ensure the technical components of the engagement are delivered to meet the customer's needs.
• Cross-Collaborate: Work with Engineers and Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement-specific product and support issues.
• Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
• Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

Requirements:

• 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 PySpark, Apache Spark, and knowledge of Spark runtime internals.
• Experience 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 white-boarding skills.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.

Preferred Qualifications:

• 10+ years of experience in data transformation and warehousing within enterprise-level, distributed data systems.
• Expertise in MLOps, ML/AI models, and AI APIs.
• Certification in a Databricks-specific domain.

Benefits:

• Comprehensive benefits and perks that meet the needs of all employees.
• Eligibility for annual performance bonus, equity, and benefits.