Senior Data Engineer
Summary
Own and operate the enterprise data platform on Azure and Microsoft Fabric, building data pipelines and Power BI dashboards to support reporting and AI-driven automation for a logistics company.
Company Summary
Priority, headquartered in Clinton Township, MI, is a pioneering technology company transforming the logistics industry with our innovative solutions & commitment to exceptional customer service. We are seeking Team Players who excel in a collaborative environment, embrace change, & understand the impact their quality of work has on others. Our company has experienced rapid growth since its founding in 2018. This growth has allowed us to continually expand our workforce. Priority operates out of several facilities across 3 states. Priority maintains a diversified business model providing service to both municipal solid-waste, construction & demolition customers. Our biggest priority is providing outstanding customer service & revolutionizing the industry through the use of the latest technology.
Job Purpose
Priority Waste is seeking a Senior Data Engineer to own the enterprise data platform that powers our reporting, dashboards, and AI-driven automation. This is a hands-on senior role reporting directly to the CTO, based on-site at our headquarters in Clinton Township, MI. You will take over an early-stage platform built on Azure and Microsoft Fabric and grow it with the company's data needs.
Duties and Responsibilities
Duties include but are not limited to:
- Own and operate the enterprise data platform end to end, from source ingestion through report-ready data.
- Build and maintain data pipelines (medallion architecture) on Azure and Microsoft Fabric.
- Integrate data from core business systems: operations, payroll, fleet management, telematics, and others.
- Model and maintain the warehouse layer that company dashboards and analytics are built on.
- Build and maintain Power BI semantic models and dashboards.
- Own platform operations: monitoring, alerting, and data quality.
- Establish and maintain data governance: shared definitions, quality standards, and access.
- Own and grow our existing AI automations for reporting and reconciliation.
- Additional duties as required.