Senior Analytics Engineer: dbt-SQL & Data Modeling

TaskRabbit, Inc.; San Francisco (CA); Hybrid; USD 110,000 - 145,000; Full time

Benefits offered by this job

Health insurance

401k match

Generous PTO

IKEA discounts

Job summary

TaskRabbit, Inc. is seeking a Senior Analytics Engineer to build and maintain data models powering company decisions. You’ll own dbt models end-to-end, ensure consistent metrics, and partner with data engineers, analysts, and business stakeholders.

The role is hands-on with mentoring responsibilities and focuses on data quality, performance, and a single source of truth for key metrics such as GMV and completed tasks. Hybrid work with SF in-office days.

Qualifications

• 2+ years of experience in analytics engineering or data engineering.
• Hands-on experience in dbt and SQL.
• Strong understanding of dimensional modeling and data warehouse design.
• Experience with orchestration tools and version control.
• Python for data pipeline development.
• Ability to translate business questions into data models.
• Strong communication skills with stakeholders.
• Mentoring engineers or leading technical projects.
• Familiarity with BI tools like Looker, Mode, or Tableau is a plus.

Responsibilities

• Design, build, and maintain scalable dbt models transformed from raw data.
• Own parts of the data model layer end-to-end.
• Collaborate with data engineers, analysts, and business stakeholders.
• Establish testing, documentation, and code review standards for dbt projects.
• Monitor data quality and performance as data volumes grow.
• Mentor junior analytics engineers and influence team practices.
• Contribute to a single source of truth for core metrics.

Skills

dbt

SQL

dimensional modeling

data warehouse design

Airflow

Git

Python

mentoring engineers

communication

Tools

Snowflake

BigQuery

Redshift

dbt Cloud

Looker

Mode

Tableau

Job description

TaskRabbit, Inc. is seeking a Senior Analytics Engineer to build and maintain data models powering company decisions. You’ll own dbt models end-to-end, ensure consistent metrics, and partner with data engineers, analysts, and business stakeholders.

The role is hands-on with mentoring responsibilities and focuses on data quality, performance, and a single source of truth for key metrics such as GMV and completed tasks. Hybrid work with SF in-office days.