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

Databricks· Engineering
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Hybrid (Washington, DC)$182k - $250.2kFull-timePosted 1mo ago

About the role

Senior Forward Deployed Engineer for federal government customers, responsible for building and productionizing data & AI solutions on the Databricks platform. Hybrid role with 20-25% travel, requiring U.S. citizenship and eligibility for a U.S. government secret clearance.

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. Work with engagement managers to scope technical delivery work with input from the customer
  • Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' 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 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.

Qualifications

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

Skills

Required:PythonScalaJavaScript/TypeScriptCloud platformsPySpark / Apache SparkCI/CDMLOps / AI models

Benefits

  • Benefits information available via region-specific document linked in the job description
Last updated Sep 10, 2026. Interested? Apply on the company site.

About Databricks

Leading Data and AI Platform for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

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