Senior Data Engineer

Responsibilities

• Build and maintain pipelines and models for client home profiles, job history, and seasonal or event-driven signals.
• Prepare data models for predictions about which home service a client will need and when.
• Connect personalization signals to email, SMS, push, onsite, CRM, and marketing channels.
• Develop dbt models and semantic layers to support and measure in-market experiments.
• Use AI coding tools to scaffold pipelines, write tests, and accelerate code review.
• Contribute to technical documentation and the roadmap for scaling the data foundation.
• Collaborate daily with Product, Design, Marketing, BizOps, Machine Learning, and Engineering partners.

Requirements

• Experience building and maintaining ELT data pipelines using tools such as dbt, Airflow, and Fivetran.
• Experience with a cloud data warehouse such as Snowflake, BigQuery, or Redshift.
• Solid data modeling skills, including dimensional modeling and star or snowflake schemas.
• Proficiency in SQL and at least one general-purpose programming language such as Python, Java, or Scala.
• Regular day-to-day use of AI coding assistants such as GitHub Copilot, Cursor, or Claude Code, including prompting, reviewing, and validating generated code.
• Comfort working with ambiguity on a discovery-stage team.
• Familiarity with BI or semantic-layer tools such as Looker, Mode, or Tableau.
• Experience with streaming platforms such as Kafka or Kinesis is a strong plus.

Benefits

• Hybrid work arrangement requiring two days per week in the San Francisco office on Tuesdays and Wednesdays.
• Employer-paid health insurance and a 401(k) match with immediate vesting for US employees.
• Generous and flexible time off, including two company-wide closure weeks.
• Taskrabbit product stipends, wellness, productivity, and education stipends.
• IKEA discounts, reproductive health support, and other perks; benefits vary by country of employment.