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Taskrabbit is a marketplace platform connecting people with Taskers for home services like furniture assembly, handyman work, and moving help. The company is owned by IKEA and operates across the US and EU with a distributed, hybrid workforce.
You'll join a small, cross-functional discovery pod (Product, Design, Marketing, BizOps, ML, Engineering) focused on client retention and personalization. Your mission: build the data foundation to predict what home service a client will need and when, then reach them proactively. This is a hands-on individual-contributor role—one level below Staff—where you'll own the design and build of specific data pipelines and models rather than set broader architectural direction.
Key responsibilities include:
- Design and maintain data pipelines and models capturing client home profiles, job history, and seasonal/event-driven signals (weather, life events, moves) feeding a predictive personalization engine
- Partner with the ML Engineer and Solutions Architect to prepare data for predictions about service needs and timing
- Build pipelines connecting personalization signals into CRM and marketing channels (email, SMS, push, onsite)
- Develop dbt models and semantic layers enabling rapid test setup and measurement for in-market experiments
- Use AI coding tools (GitHub Copilot, Cursor, Claude Code) as a default workflow component to scaffold pipelines, write tests, and accelerate code review
- Contribute to technical documentation and roadmap planning for scaling if the team's bets succeed
- Collaborate daily with Product, Design, Marketing, BizOps, and ML partners in a fast-moving pod
You'll need solid experience with modern data tools (dbt, Airflow, Snowflake or equivalent), cloud data warehouses, dimensional modeling, SQL, and at least one general-purpose programming language (Python, Java, Scala). Critically, you must actively use AI coding assistants in your workflow—not as optional—and know how to prompt, review, and validate AI-generated code. Comfort with ambiguity and fast iteration in a discovery-stage environment is essential. Familiarity with BI tools or semantic layers is a plus.
The role is hybrid, requiring 2 days in office (Tuesdays & Wednesdays) at the San Francisco hub (130 Sutter St). Candidates must be legally authorized to work in the US without employer sponsorship.
