Data Engineer (Hybrid)

The role – what you’ll do 

Barr is seeking a Data Engineer to join our Minneapolis, Minnesota, team. In this hybrid role, you will support the Information Systems group, playing a key part in designing and maintaining reliable data pipelines, integrating with third-party systems and APIs, and contributing to the evolution of our ETL architecture across a variety of use cases. You’ll collaborate with cross-functional teams, including data scientists and machine learning engineers, to align data strategies with AI objectives. 

A successful person in this role is curious and proactive about exploring new data technologies that support innovation in AI and analytics. They enjoy partnering with cross-functional teams and using their expertise to help define practical strategies that improve data quality, maintainability, and reliability while supporting the organization’s growing needs around AI readiness and emerging technologies. This person also enjoys collaboration and brings a thoughtful approach to data engineering. 

Your impact – key responsibilities 

• ETL development and maintenance: Troubleshoot, maintain, and monitor ETL processes built with SQL Server Integration Services (SSIS), Python, or other processes. Review existing ETL patterns to identify areas for optimization, make recommendations, and contribute to the redesign of integration workflows.

• Data observability and monitoring: Improve traceability by building audit and logging capabilities into ETL pipelines. Partner with teams to strengthen observability by improving alerting, error handling, and operational dashboards that keep ETL health visible and actionable.

• Integration architecture: Architect and support robust API and point-to-point integrations with internal and third-party systems—bridging data silos and unlocking smoother automation across software tools.

• DevOps and change management: Contribute and manage structured change management and version control practices using Azure DevOps to support consistent development and deployment of ETL workflows.

• Data engineering standards and best practices: Help set the tone for data engineering excellence by guiding best practices in pipeline structure, metadata usage, and data quality—helping ensure each workflow is built to scale and evolve. 

About the opportunity 

• Compensation: Anticipated range of $98,000–115,000 annually. Compensation will vary based on relevant experience, education, skill level, and other compensable factors. Employees in this position may also be eligible for a discretionary cash bonus based on team and individual performance. This position is classified as exempt under the Fair Labor Standards Act.

• A hybrid work arrangement may be considered for this position. A hybrid work arrangement refers to splitting time worked between a Barr office and a home office. This position is based out of Barr's Minneapolis, Minnesota, office. 

About you – required core competencies  

• Education: Bachelor’s degree in computer science, data engineering, information systems, or a related field or equivalent experience.