Top Data & Analytics Jobs in Minneapolis–Saint Paul, MN

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

The Data Analyst will build performance reporting tools, automate data processes, conduct ad-hoc analyses, and provide insights for company initiatives.

The Senior Business Analyst will lead end-to-end process discovery and define workflows utilizing AI and automation to improve operational efficiency.

The Senior Data Center Administrator is responsible for data center operations including inventory management, logistics, vendor coordination, and capacity planning. The role requires technical expertise and strong communication skills to ensure efficient data center environments across multiple locations.

The Cloud Data Architect will design scalable data architectures for SaaS solutions, set data standards, collaborate with engineering, and ensure data governance and optimization. Requires advanced SQL and cloud platform proficiency.

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

Lead a team of data and infrastructure engineers to develop cloud-based data systems and solutions for analytics, ensuring best practices in data management and MLOps.

The Data Engineer will help build modern data infrastructure, designing ETL pipelines, modeling datasets, and collaborating with teams for improved data quality and accessibility.

Responsible for acquiring and maintaining high-quality civic data, designing data workflows, leading end-to-end projects, and ensuring data reliability and quality.

The Senior Data Engineer will design and manage data pipelines, work with complex datasets, and collaborate with teams to enhance data product integrity and effectiveness.

The Manager, Data Success Management oversees Data Success Managers, manages data operations, supports partners, improves workflows, and ensures data quality.

The Data Scientist will build analytics infrastructure, conduct analysis and modeling, and collaborate with teams to enhance data impact and insights. Responsibilities include exploratory analysis, model building, and maintaining datasets for student success and operational efficiency.