Senior Architect - Forward Deployed Engineering

About the role

Databricks is hiring a Forward Deployed Engineer (FDE) Senior Architect in London. As an FDE you work with customers to build and productionize solutions to their data and AI challenges using the Databricks platform, owning the architecture, leading design decisions and implementing end-to-end systems spanning data engineering, AI and application development. The role is hands-on and customer-facing, and FDEs are billable.

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, and scope technical delivery with engagement managers
• Embed with customer teams, from technical ICs to executives, to understand challenges and deliver impact
• Own architecture and design decisions, keeping solutions secure, scalable and aligned with customer needs and Databricks best practices
• Work with the 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
• Contribute accelerators, frameworks and best practices that scale across accounts and influence the product roadmap

Required profile

• Strong experience in data engineering, data platforms and analytics, or software engineering
• 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
• Curiosity and adaptability, with a willingness to learn new technologies needed to deploy Databricks-based solutions
• Travel to customers about 20% of the time; Databricks certification preferred but not essential

Required skills

• 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 its runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps, ML/AI models and AI APIs
• Ability to design and deploy performant end-to-end data architectures combining pipelines, ML/AI models and user-facing interfaces
• Documentation and white-boarding skills