Analytics Engineer

SupplyHouse is hiring an Analytics Engineer for its Finance team to build and own the production data transformation layer in BigQuery. The role will establish tested, documented datasets and standardized business metrics to support trusted, self-service analytics across the organization.

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:

• Bachelors 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
• Applicants must be currently authorized to work in the U.S. on a full-time basis. SupplyHouse.com will not sponsor applicants for work visas
• 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