Analytics Engineer

supplyhouse; United States; Remote; USD 72,000 - 91,000; Full time

Job summary

SupplyHouse is building the production data layer to turn 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 include developing a layered, production-ready warehouse model in the cloud, consolidating logic into governed models, and defining metrics with stakeholders.

Qualifications

• 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.

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.

Skills

SQL skills

Data modeling

Git & CI

Analytics mindset

Education

Bachelor’s degree in a quantitative/technical field

Tools

dbt

Dataform

BigQuery

Google Cloud

Job description

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.