Top Data & Analytics Jobs in Ann Arbor, MI

In this role, you will design data architecture, lead integration strategies, mentor engineers, and drive AI infrastructure for cross-division data systems.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

The Senior Data Analyst will analyze digital marketing campaigns, leverage data sources for business decisions, and communicate insights effectively to improve performance and support Media Partners.

Lead alignment of technology and business strategies to improve payments reporting, forecasting, and operational planning. Build and maintain reports, dashboards, and models using BI tools and SQL, perform variance analysis, drive data standardization and quality, support migration to modern reporting platforms, and produce ad hoc analyses to inform decision-making.

Lead design and delivery of large-scale quantitative and qualitative market research studies, manage client accounts, develop RFPs, mentor research managers, ensure project quality, timelines, and provide strategic recommendations and reports.

Analyze historical and real-time staffing and appointment data to forecast resource needs, build staffing plans, create reports/dashboards and process maps, and collaborate with leadership, HR, and training to optimize scheduling and staffing levels.

Develop and maintain operational BI dashboards and ETL workflows in Domo and Redshift, analyze claims data, validate datasets, provide actionable insights to stakeholders, and mentor other analysts.

Own and evolve revenue systems (Salesforce, CPQ), build and govern the enterprise data platform, drive systems integration and AI enablement, manage HRIS and vendor relationships, and lead a cross-functional team supporting Finance, HR, Sales, Operations, and Customer Success.

Manage design, development, and delivery of data products and analytics solutions. Lead and coach an analytics team, gather requirements, improve processes, reduce technical debt, collaborate with platform and product architecture, and ensure solutions meet internal and external client needs.

Design, build, and maintain scalable ETL and data pipelines on AWS using Python/PySpark. Develop Glue/Lambda/Step Function workflows, event-driven integrations, and data lake/warehouse solutions. Tune SQL, implement monitoring/validation, support API/JSON integrations, troubleshoot operations, document and automate deployments, and mentor junior engineers.