Sr. Forward Deployed Engineer - Public Sector

The shape of it

In the posting’s own words

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. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.

What it asks for · 9

• 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 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 white-boarding skills
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range Preferred Qualifications

Also a plus

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

What the job covers

• 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.

Tools and skills named

Words the posting leans on

• customer19×
• data10×
• technical8×
• architecture6×
• projects6×
• design5×
• engineering5×
• impact5×
• experience4×
• lead4×
• product4×
• applications3×
• deliver3×
• delivery3×
• deployment3×
• end-to-end3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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