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# Analytics Engineer

- **Company:** DATA ENGINEERING, LLC
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $110,000.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Airflow, Business Logic, BigQuery, Cloud Computing, Code Review, Information Engineering, Data Warehousing, Dimensional Modeling, Python (Programming Language), Raw Data, Standard Sql, Tableau (Software), Workflow Management Systems, Snowflake, Git, Looker Analytics, Software Version Control, Data Pipelines
- **Published:** September 29, 2026
- **Apply:** https://startup.jobs/analytics-engineer-taskrabbit-10219183

## About the Role

* 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 tools such as Looker, Mode, or Tableau is a plus
 * Experience with marketplace or on-demand business models is a plus

## Description

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)


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