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Salary: USD 110,000 - 145,000 / annual
Taskrabbit is a marketplace platform connecting people with Taskers for everyday home services like furniture assembly, handyman work, and moving help. The company is owned by IKEA and operates as a hybrid organization with employees across the US and EU.
You will join Taskrabbit's Data Engineering team as a Senior Analytics Engineer, a hands-on individual-contributor role at the intersection of data engineering and analytics. You'll own key parts of the data model layer end-to-end, building and maintaining the data models that power decision-making across the company. Your work will transform raw data into trusted, well-documented datasets that business teams rely on daily.
Key responsibilities include:
- 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)
The role is hybrid, requiring 2 days in office at the San Francisco hub every Tuesday and Wednesday (130 Sutter St, San Francisco, CA).
REQUIREMENTS:
- 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
- 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 tools such as Looker, Mode, or Tableau is a plus
- Experience with marketplace or on-demand business models is a plus
