Director of Data Engineering

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 remote-first company with employees distributed across the US and EU
• 5-time Best Places to Work in 2022 by BuiltIn. Including Best Companies in SF, Best Mid-Sized Companies, and Best Benefits
• DataBird journal’s “Best Places” Best Companies for Diversity, #1 2019 and 2020
• DataBird journal’s “Best Places” Best Companies for Women, #4 2019 and #1 2020

Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed!.

This is a Hybrid role with the expectation that employees will begin working 2 days per week in our dedicated office space in San Francisco or New York City starting in September of 2025. 

About the Role

Data is the lifeblood of Taskrabbit, and we are looking for a visionary leader to join as our Director of Data Engineering. In this critical role, you will own the data infrastructure that powers our entire business. You will be responsible for hiring, coaching, and directly managing the Data Engineering and Analytics Engineering teams, guiding them to design and build high-scale, reliable systems that ensure data accuracy, availability, and trustworthiness.

As the Director of Data Engineering, you will be the senior-most engineer in the data organization, responsible for setting the vision, strategy, and standards for our data platform. You will implement best-in-class data warehousing practices, manage data governance, and create robust processes for data monitoring, alerting, and anomaly detection. You will partner closely with leaders across Data Science, Machine Learning, Product, and Engineering to define your team's roadmap, prioritize high-impact work, and deliver against timelines with high-quality software. This is a strategic role that requires a blend of deep technical expertise, strong leadership skills, and a passion for building the foundational systems that enable a data-driven culture.

What You'll Work On:

• Team Leadership & Development: Build, coach, and scale a high-performing, geographically distributed team of data and analytics engineers, fostering a culture of excellence, innovation, and accountability.
• Strategic Vision & Roadmap: Proactively drive the vision for Taskrabbit's data platform. Define and execute a strategic roadmap that aligns with our broader data strategy and company objectives, focusing on scalability, reliability, and efficiency.
• Engineering & Architectural Excellence: Promote data engineering best practices (CI/CD, coding, testing, observability, security) for maintainable, high-quality solutions. Lead data model design and define data warehousing best practices, overseeing foundational improvements.
• Enable Self-Service Analytics: Champion and oversee the development of a semantic layer to provide a single source of truth for key business metrics, empowering teams across the company with self-service analytics capabilities.
• Cross-Functional Partnership: Build strong, collaborative relationships with Data Scientists, Product Managers, and Software Engineers to understand their evolving data needs and deliver robust solutions.
• Operational Excellence: Define and manage SLAs for all critical datasets and production processes. Implement and oversee a comprehensive observability strategy, including monitoring, alerting, and data quality checks.
• Establish and Oversee Data Governance & Compliance: In collaboration with the Information Security Committee, establish and enforce data lifecycle management policies, including data retention and disposal procedures. Lead initiatives to ensure the data platform meets and maintains compliance with global regulations.
• Ensure Data Reporting Correctness and Accuracy: Implement a robust data quality framework to guarantee accurate, consistent, and reliable data for reporting and analysis. This involves defining data quality me