About the Role
As a Forward Deployed Engineer (FDE) at Databricks, you will partner with customers to develop and productionize solutions for their data & AI challenges using the Databricks platform. This role involves owning the architecture, leading design decisions, and implementing end-to-end systems that encompass data engineering, AI, and application development. You will collaborate cross-functionally with engineering, product, and developer relations to influence long-term strategic priorities. FDEs operate with customer empathy, integrating with client systems, providing training, and addressing technical needs to maximize customer value from their data. This is a hands-on, customer-facing position for engineers who excel at the intersection of technology and business impact, combining engineering expertise with adaptability, curiosity, and a passion for problem-solving.
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 in implementing 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 with customer input.
- Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects to facilitate 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
- 6+ years 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.
- Ability to 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.