Analytics Engineer

Who You Are You’re an engineer who likes turning business questions into reliable, well-structured data. You build and maintain models people can trust, investigate issues through to their source, and take responsibility for how changes affect downstream users and assets. You’re comfortable working directly with business partners and a small data team. About The Role This role reports to the Director of Enterprise Data & Analytics and works closely with business teams, analysts, and data engineers. You’ll develop governed data models and reusable data products that support reporting and automations. You’ll also help improve how data products are reviewed, released, and maintained as the company and its data environment grow. Other responsibilities include: Build and maintain dbt models and certified data marts for key business domains. Work with business partners and analysts to turn requirements into clear data definitions, models, and measures. Establish consistent business logic for shared metrics and dimensions. Build and maintain data quality tests; investigate failures and trace issues to their source. Document model purpose, ownership, definitions, dependencies, and known limitations. Assess downstream effects before changing models, metrics, or source assumptions. Use Git and established review and deployment practices to release changes safely. Support the datasets and semantic models used in the reporting layer and applications. Improve existing models and workflows as business needs and source systems change. Communicate tradeoffs, dependencies, and delivery risks to technical and business partners. Complete ongoing security awareness training and comply with company policies. Identify and escalate security risks to the appropriate Executive Leadership Team member and actively contribute to remediation efforts. Other duties as assigned Desired skills and experience: Strong SQL skills and experience building production data models. Hands-on experience with dbt or a comparable transformation framework. Experience with a cloud data warehouse such as Snowflake, BigQuery, or Redshift. Strong experience designing dimensional models and data marts. Experience testing, documenting, and maintaining data models. Familiarity with Git and collaborative code review and release practices. Ability to investigate data discrepancies and explain their causes. Ability to work with business partners to clarify requirements and resolve differences in metric definitions. Strong communication, documentation, and follow-through. Preferred Experience Python for data tasks or automation. Supporting data integration related to mergers and acquisitions. Owning a semantic model. Master data management. IT, VAR, distribution, or supply chain data experience. What Success Looks Like Core business data is organized into documented, tested, reusable models and marts. Teams use consistent definitions for shared metrics. The creation of an internal marketplace for certified datasets. Data issues are investigated and resolved at their source where possible. Changes are reviewed, tested, and assessed for downstream effects before release. Analysts and business partners can find and understand the data products they need. Ownership and model logic are clear enough that the work does not depend on undocumented knowledge held by one person. A Little About Us Our mission is to challenge and enable our employees to achieve great things. We live and breathe our core values: We Before Me: We demonstrate empathy through our actions and solicit diverse voices and opinions. We put ourselves in each other’s shoes, readily admit our mistakes, and generously share our time and knowledge. Dare To Be Great: We are big-picture thinkers who focus on solutions to problems. We solicit and offer actionable feedback to others without hesitation. We embrace opportunities