Senior Director, Data

About Taskrabbit:

Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more.

At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world.

Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed!

This role operates on a hybrid schedule requiring two days of in-office collaboration per week. The position can be based in either our San Francisco office or our new New York City office (opening January 2026).

About The Role:

Taskrabbit is at a pivotal moment in our journey, transforming our data capabilities from a supporting function into a strategic driver of growth and innovation. We're seeking a visionary and highly accomplished Senior Director of Data to lead this critical transformation. This is a unique opportunity to build a best-in-class data organization, embed a data-driven culture, and unlock significant business value by leveraging our most valuable asset: data.

Reporting directly to CPO, you will be responsible for defining and executing Taskrabbit's overarching data strategy. You will lead and scale a diverse and talented team encompassing the current teams Data Science, Data Engineering, Machine Learning Engineering, and Product Analytics, ensuring a cohesive, high-performing, and impactful data ecosystem.

What You'll Work On:

• Define and Execute Data Strategy: Own, champion, and evolve Taskrabbit's data strategy, aligning it with the overall business strategy, our OKRs, and our long-term Product Vision. This includes advancing foundational projects like implementing our semantic layer and modernizing financial data architecture.
• Drive Business Outcomes: Partner closely with EDDP (Engineering, Design, Data, Product) leaders and key business stakeholders to identify high-impact opportunities where data can drive tangible business results. You'll be accountable for measuring and delivering on the commercial impact of data initiatives, ensuring our efforts directly contribute to revenue growth, operational efficiency, and enhanced customer experience.
• Lead and Grow a Diverse Team: Provide exceptional leadership and mentorship to managers and individual contributors across Data Science, Data Engineering, Machine Learning Engineering, Analytics Engineering, and Product Analytics. Foster a culture of technical excellence, collaboration, innovation, and continuous learning. Attract, hire, and retain top talent.
• Drive Organizational Design & Optimization: Assess current team structures, roles, and responsibilities within the data organization. Strategically restructure team composition, reallocate resources, and redefine roles as necessary to optimize for efficiency, accelerate delivery on strategic data objectives, and better align with the evolving needs of the business.
• Establish Data Governance and Quality: Implement robust data governance frameworks, including data ownership, quality management processes, standards, and policies (e.g., data standards, classification, access, retention). Drive proactive data quality management, ensuring accuracy and trustworthiness of data across the organization, from source to consumption.
• Modernize Data Infrastructure: Oversee the strategic development and ongoing enhancement of our data platform and infrastructure (Snowflake, Airflow, dbt, etc.). This includes establishing production data model monitoring, and simplifying/consolidating redundant systems.
• Drive Advanced Analytics & ML Capabilities: Lead the development and deployment of cutting-edge data science and machine learning solutions that directly impact product features, marketplace dynamics (e.g., pricing, matching), and operational efficiency. Establish standardized MLOps practices and a robust experimentation culture.
• Empower Self-Service & Data Literacy: Develop a comprehensi