Partner Engineer

RDQ427R535

At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. 

About the Role

This partner intelligence engineer owns the internal tooling that runs the ISV partner organization: the pipelines, dashboards, Genie spaces, metric views, and the AI applications and workflows we use to operate the partner business. You will build and maintain that stack on Databricks and use the platform heavily, every day. You will also work with the Apps and AI teams as an early user of new features, and with Developer Relations to share what you build. The role is based in San Francisco and reports into Partner Engineering.

Impact you will have 

• Data pipelines and quality: Build, schedule, and maintain the data pipelines that run the partner business, and own their quality, monitoring, and governance.
• Partner metrics and measurement: Own how we measure partners: the metrics, metric views, and definitions that serve as the source of truth for partner performance and health.
• Reporting and self-serve analytics: Build and maintain the dashboards, Genie spaces, and apps the team uses to run the business day to day.
• Internal AI apps: Build AI applications and agentic workflows that automate how we run the partner business.
• Partner AI platforms: Build real internal tools on partner products like Replit, Lovable, Cursor, Claude, and Codex, and bring what you learn about their strengths and gaps back to the AI and Apps partnerships.
• Early Databricks adopter and DevRel: Try new Databricks features early (Apps, Genie, metric views, AI/BI, Lakebase, Agent Bricks), give product teams direct feedback, and work with Developer Relations to turn what you build into reusable examples.

Required Qualifications

• 3+ years in data engineering, analytics engineering, or a similar hands-on data or AI role. 
• Heavy hands-on production experience with Databricks data engineering and analytics tool
• Strong SQL and Python, with experience building and maintaining production data pipelines.
• Experience building the analytics layer a team runs on: dashboards, semantic or metric layers, and clear metric definitions.
• Experience building AI applications or agentic workflows (LLM-powered apps and automations).
• Regular hands-on use of AI code-gen and app-building tools (Replit, Lovable, Cursor, Claude, Codex). You use them in your day-to-day work.
• Clear communicator who works well in fast-moving, sometimes ambiguous situations. 
• Strong propensity for GSD → Gets Stuff Done!

Preferred 

• Depth in Databricks analytics and AI features: Genie, AI/BI, metric views, Lakebase, Agent Bricks.
• dbt or a similar transformation framework, and modern analytics-engineering practices.
• Experience defining business metrics and KPI frameworks.
• Open-source contributions or community work in data and AI.