Analytics Engineer

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About the role

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, 2025) 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! Prior to applying please note: • We are currently unable to provide visa sponsorship for this position (including H-1B, OPT, F1, CPT or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. • This role is hybrid, requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St, San Francisco, CA). About the Role Taskrabbit's Data Engineering team is looking for a Senior Analytics Engineer to build and maintain the data models that power decision-making across the company. You'll sit at the intersection of data engineering and analytics — turning raw data into trusted, well-documented datasets that business teams rely on every day. This is a hands-on, individual-contributor role: you'll own key parts of the data model layer end to end, partnering closely with data engineers, analysts, and business stakeholders to keep our metrics consistent and our warehouse trustworthy. What you will work on • Design, build, and maintain scalable dbt models that transform raw data into clean, tested, well-documented datasets • Own key parts of the data model layer, from source to mart, ensuring consistency in business logic and metric definitions across the warehouse • Partner with data engineers, analysts, and business stakeholders to understand reporting needs and translate them into reliable data pipelines • Establish and enforce testing, documentation, and code review standards for dbt projects • Monitor data quality and freshness, and troubleshoot discrepancies when numbers don't match across reports • Improve query performance and warehouse efficiency as data volume grows • Mentor junior analytics engineers and contribute to team best practices and tooling decisions • Help define and maintain a single source of truth for core business metrics (e.g., GMV, completed tasks, take rate) Requirements + Areas of Expertise • 2+ years of experience in analytics engineering, data engineering, or a related role, with deep hands-on experience in dbt and SQL • Strong understanding of dimensional modeling and data warehouse design (Snowflake, BigQuery, or Redshift experience preferred) • Experience with orchestration tools (e.g., Airflow, dbt Cloud) and version control (Git) • Working knowledge of Python for data pipeline development and automation • A track record of translating ambiguous business questions into clear, well-structured data models • Strong communication skills — able to explain technical tradeoffs to both engineers and non-technical stakeholders • Experience mentoring other engineers or leading technical projects • Familiarity with BI or semantic-layer t

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