Top Senior Level Data Engineer Jobs in Minneapolis, MN

As a Senior Machine Learning Engineer at Wasabi, you will develop and refine computer vision algorithms and NLP models while leading AI advancements in a team-oriented environment. Responsibilities include collaborating across teams, optimizing machine learning models, and ensuring reliable implementation and maintenance of AI systems.

The Senior Machine Learning Engineer at Samsara will be responsible for developing ML solutions to enhance the safety, efficiency, and sustainability of physical operations. This remote position requires working closely with engineering teams to deliver core infrastructure and services.

In this role, the Marketing Data Engineer will architect scalable ETL/ELT pipelines, manage cloud-based data warehouses, and develop data integration solutions. Responsibilities include collaborating with various teams to support analytics, ensure data quality, and optimize performance across data workflows.

The Marketing Technology Data Engineer will design and build data solutions for managing and integrating real-time and batch data, focusing on data quality and availability for enterprise clients. The role involves developing data pipelines, implementing CI/CD processes, and collaborating with teams to meet client needs while leveraging Google Cloud services.

Lead data engineer role at Wipfli focusing on the continuous advancement of a modern data lakehouse. Responsible for translating requirements into effective data models, developing in data technologies, managing project life cycle activities, achieving/maintaining proficiency in required skills, and collaborating with team members.

The Senior Data Engineer will lead the development of high-impact products, collaborate with Finance and Accounting teams, and take ownership of data services lifecycle. Responsibilities include architecting data models, resolving data integrity issues, and ensuring data solutions align with business needs.

The Senior Data Engineer will design, develop, and manage scalable data architectures and pipelines, primarily using cloud platforms like Azure. Responsibilities include data integration, modeling, optimization, and mentoring. The role emphasizes collaboration with cross-functional teams to ensure data infrastructure supports analytics and drives decision-making.