Analytics Engineer

Role overview Build the production data layer that turns raw business information into reliable, reusable datasets for analytics. You’ll shape how core metrics are defined and reported, working with analysts, business partners, and IT to make trustworthy self-service reporting possible.

Responsibilities - Develop and maintain a layered, version-controlled warehouse model using SQL and a transformation framework. - Move business logic from numerous standalone scheduled queries into shared, tested, governed models. - Establish consistent definitions for key business metrics with stakeholders. - Add automated quality checks and continuous integration so changes are validated before release. - Document datasets, metric definitions, and lineage, and support accurate raw-data ingestion with IT. - Help assess the future reporting and BI layer.

Requirements - Bachelor’s degree in a quantitative, technical, or related discipline. - At least two years of data modeling experience. - Strong SQL skills and experience creating production data models in a cloud warehouse. - Practical experience with a transformation framework such as dbt or Dataform. - Familiarity with Git, code review, testing, and continuous integration applied to analytics work. - Experience with layered or dimensional models and maintainable, documented datasets.

Nice to have - Experience with BigQuery, Google Cloud Dataform, or building a data or semantic layer from scratch. - Familiarity with cloud tooling or distribution, e-commerce, HVAC, or plumbing data.

Benefits and work setup - Remote, full-time weekday role, with eligibility limited to a set of U.S. states and six annual trips to the New York headquarters. - Starting base salary is listed as $72,440–$90,550, within a broader range up to $108,660. - Benefits include medical, dental, and vision coverage; retirement matching; paid leave; home office equipment and stipend; and a professional development budget.