Senior Forward Deployed Engineer (Fullstack)

About the role

Databricks is hiring a Senior Forward Deployed Engineer (FDE) to work with customers and build and productionize solutions to their data and AI challenges using the Databricks platform. The role is hands-on and customer-facing, combining engineering expertise with customer empathy, and is billable: engineers deliver projects according to specification. Locations listed are Belgrade, Munich and Zurich.

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
• Embed with customer teams, from technical staff to executives, to understand challenges and deliver impact
• Lead 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

• 6+ years of 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 range of stakeholders
• Ability to travel to customers about 20% of the time
• Databricks certification

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 end-to-end data architectures combining data pipelines, ML/AI models and user-facing interfaces
• Documentation and white-boarding skills