Senior Forward Deployed Engineer (Technical Data Architect)

About the role

Databricks is hiring a Senior Forward Deployed Engineer (Technical Data Architect) in London, working in a hybrid setting. As a Forward Deployed Engineer (FDE), you work with customers to build and productionize solutions to their data and AI challenges using the Databricks platform. You own the architecture, lead design decisions and implement end-to-end systems spanning data engineering, AI and application development, and you are billable, completing projects to specification.

Key responsibilities

• Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications and data ingestion and ML/AI model integration.
• Guide strategic customers through big data and AI projects, from end-to-end design and build to deployment, working with engagement managers to scope technical delivery.
• Advise customers on architecture and design, and bootstrap or implement projects that lead to adoption of Databricks.
• Lead architecture and design decisions so solutions are secure, scalable and aligned with customer needs and Databricks best practices.
• Work with the Databricks technical team, Project Manager, Architect and Customer team to deliver the technical components of each engagement.
• Work with Engineering and Customer Support to give product and implementation feedback and help resolve engagement-specific issues quickly.
• Embed with customer teams, from technical ICs to executives, to understand challenges and deliver impact.
• Contribute accelerators, frameworks and best practices that scale across accounts and influence the product roadmap.

Required profile

• Experience in data engineering, data platforms and analytics, or software engineering / full stack development.
• Experience with technical project delivery: managing scope, timelines and measurable outcomes, and turning complex concepts into actionable solutions.
• Experience working with enterprise clients and managing conflicts across a broad stakeholder range.
• Ability to travel to customers about 20% of the time.
• Curiosity and adaptability, with a willingness to build skills in technical areas and explore new technologies.
• Databricks certification is an advantage.

Required skills

• Writing code in Python, Scala, JavaScript/TypeScript and modern frameworks.
• Working knowledge of at least two cloud ecosystems (AWS, Azure, GCP), with expertise in one.
• Deep experience with distributed computing with Apache Spark and knowledge of its runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models and AI APIs.
• Design and deployment of production data architectures combining data pipelines, ML/AI models and user-facing interfaces.
• Documentation and white-boarding skills.