About the Role
As a Forward Deployed Engineer (FDE), you will work with 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. This role involves cross-functional collaboration with engineering, product, and developer relations to shape long-term strategic priorities. FDEs deliver with customer empathy, integrating with client systems, providing training, and addressing other technical needs to help customers maximize value from their data.
This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. 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. FDEs are billable and complete projects according to specification with exceptional customer empathy.
The Impact You Will Have
- 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 customer input.
- Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects leading to their 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.
- Work with the Databricks technical team, Project Manager, Architect, and Customer team to ensure technical components of the engagement meet customer needs.
- Work with Engineering and Databricks Customer Support to provide product and implementation feedback and 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.
What We Look For
- Extensive experience in data engineering, data platforms & analytics, or software engineering.
- Comfortable writing code in either 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 - managing scope, timelines, and measurable outcomes, translating complex concepts into actionable solutions.
- Documentation and white-boarding skills.
- Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
- Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
- Ability to travel to customers 20% of the time.
- Databricks Certification.