Partner Engineer: Partner Intelligence, AI & Apps

Databricks Databricks · Data AI · San Francisco, CA · Product

Partner Engineer role focused on building internal tooling for the ISV partner organization using Databricks. This includes data pipelines, dashboards, and AI applications/agentic workflows. The role also involves using and providing feedback on new Databricks features and building tools on partner AI products.

What you'd actually do

  1. Build, schedule, and maintain the data pipelines that run the partner business, and own their quality, monitoring, and governance.
  2. Own how we measure partners: the metrics, metric views, and definitions that serve as the source of truth for partner performance and health.
  3. Build and maintain the dashboards, Genie spaces, and apps the team uses to run the business day to day.
  4. Build AI applications and agentic workflows that automate how we run the partner business.
  5. 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.

Skills

Required

  • 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!

Nice to have

  • 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.

What the JD emphasized

  • Heavy hands-on production experience with Databricks data engineering and analytics tool
  • 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.

Other signals

  • Build AI applications and agentic workflows
  • Build internal tools on partner products like Replit, Lovable, Cursor, Claude, and Codex
  • Regular hands-on use of AI code-gen and app-building tools