Sr. Forward Deployed Engineer (FDE) - Public Sector
Databricks2 months ago
Base Salary
$182k - $250k/yr
Responsibilities
- Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integrations.
- Guide strategic customers through the end-to-end design, build, and deployment of big data and AI applications.
- Scope technical delivery work with customers and engagement managers.
- Advise customers on architecture and design and help bootstrap or implement their Databricks projects.
- Own architecture and design decisions to ensure solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
- Deliver technical engagement components in collaboration with Databricks engineers, project managers, architects, and customer teams.
- Collaborate with engineering and customer support to provide product and implementation feedback and resolve engagement-specific issues.
- Embed with customer teams and engage stakeholders ranging from technical individual contributors to executives.
- Create reusable accelerators, frameworks, and best practices that scale across accounts and influence the Databricks product roadmap.
- Provide customer training and other technical support needed to drive adoption and value.
Requirements
- Active Secret or Top Secret clearance is required.
- 6+ years of experience in data engineering, data platforms and analytics, or software engineering.
- Fluency writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks.
- Working knowledge of at least two cloud ecosystems—AWS, Azure, or GCP—with expertise in at least one.
- Deep experience with distributed computing using 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 and applications combining data pipelines, ML/AI models, and user-facing interfaces.
- Experience with technical project delivery, documentation, and whiteboarding.
- Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
- Preferred: expertise in MLOps, ML/AI models, and AI APIs.
- Preferred: Databricks Certification.
Benefits
- Hybrid work arrangement with travel to customer locations 20–25% of the time
- Comprehensive benefits and perks, with regional details provided by Databricks
Tech Stack
Categories
Data EngineeringForward Deployed
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.