Analytics Engineer

We are looking for an Analytics Engineer to join our Finance team. This individual will report into our Senior Manager of Data Analytics and will design and build SupplyHouse’s production data layer from the ground up in BigQuery. They will own the transformation layer between raw data and reporting, turning complex data into clean, tested, and well-documented datasets, standardizing core business metrics, and enabling trusted, self-service analytics across the organization. If you’re passionate about building reliable data foundations, enjoy partnering with engineers, analysts, and business stakeholders, and are excited to make high-quality data more accessible and actionable across an organization, we’d love to hear from you!

This remote position is open to individuals who live in, or are open to relocating to, the following states: Arizona, Delaware, Florida, Georgia, Kentucky, Nevada, New Jersey, New York, North Carolina, Ohio, Rhode Island, South Carolina, Tennessee, Texas, Virginia, and Washington.

This position requires travel to our headquarters in Melville, NY 6 times per year for internal meetings and team building activities. We reimburse reasonable and necessary travel expenses, and you’re also welcome to work on-site anytime beyond these visits – our doors are always open.

Responsibilities:

• Design and build a layered, version-controlled data model in BigQuery using a modern transformation framework (Dataform).
• Migrate business logic out of hundreds of ad hoc scheduled queries into governed, reusable, tested models.
• Work with the team to define and own the canonical definitions of core business metrics.
• Implement automated data testing and continuous integration so data quality is enforced before changes ship.
• Document models, definitions, and data lineage so knowledge lives in the system.
• Partner with analysts and business stakeholders to build a foundation that supports reliable self-serve reporting.
• Partner with IT to support accurate and timely raw data ingestion from the IT side.
• Help evaluate and shape the go-forward BI layer, given that the current Power BI setup is open to reconsideration.

Requirements:

• A Bachelor's degree in a quantitative, technical, or related field.
• 2+ years of data modeling experience.
• Strong SQL skills and hands-on experience building production-ready data models within a cloud data warehouse.
• Hands-on experience using a data transformation framework, such as dbt, Dataform, or a comparable tool.
• Software engineering fundamentals applied to analytics: version control (Git), testing, code review, and CI.
• Layered or dimensional data modeling experience, with a track record of maintainable, well-documented datasets.

Preferred Qualifications:

• Experience working with Google BigQuery as a cloud data warehouse.
• Experience using Google Cloud Dataform to build and manage data transformations.
• Direct experience standing up a data model or semantic layer from scratch.
• Familiarity with Google Cloud tooling and Dataform specifically.
• Exposure to distribution, e-commerce, HVAC, or plumbing data domains.