Top Senior Data & Analytics Jobs in Detroit, MI

Manage GTM analytics strategy, lead a team of analysts, define data governance, develop forecasting models, and deliver insights to drive revenue growth.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

The role involves analyzing insurance classification frameworks, creating mapping documentation, and communicating classification rationale while working with stakeholders.

Lead and develop teams for hands-on labs, improving learning strategies and operational efficiency while collaborating across departments. Shape the future of technical learning and manage production operating models.

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.