Top Data & Analytics Jobs in Ann Arbor, MI

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.

Designs and maintains scalable cloud data architectures, pipelines, ETL processes, data warehouses, databases, and data models. Ensures data quality, accuracy, security, availability, and consistency across sources. Develops SQL queries for analytics and reporting, and documents pipelines, schemas, architectures, and models. The role requires expertise with Python, Java, Scala, R, SQL, relational and NoSQL databases, cloud platforms, and Snowflake.

Design and build scalable data engineering and AI agent governance capabilities across major cloud AI platforms. Develop ingestion, processing, ETL, observability, security, lifecycle management, and identity governance features. Evaluate emerging AI agent frameworks and interoperability standards, troubleshoot customer issues, document architecture and processes, and collaborate with engineering, security, compliance, product, and support teams. The role also involves improving distributed data systems, mentoring engineers, and leading technical initiatives.

Establish and operationalize Finance data governance across Finance and Technology. Define governance models, business glossaries, data inventories, lineage, quality controls, master-data standards, hierarchies, and reconciliation processes. Support SAP, Snowflake, reporting, planning, and analytics data products; facilitate stakeholder workshops; document requirements; manage governance backlogs; and coach data owners and stewards in an ambiguous enterprise environment.

Own and build Underdog’s regulatory reporting data platform, including dbt models, resilient pipelines, automated validations, monitoring, and reporting roadmaps. Partner with regulators, engineering, product, compliance, and leadership; lead audits, investigations, root-cause fixes, data governance, and on-call operations. WOOF WOOF.

Analyze marketing and media data to measure TV and streaming campaign effectiveness, validate data and assumptions, identify actionable insights, and create clear visualizations and client-ready presentations. The analyst will use Excel, BI and data platforms, SQL, and AI tools to accelerate analysis while independently validating results and explaining methodologies, KPIs, and recommendations to internal teams and clients.

Leads internal data analysis projects, identifies business opportunities and risks, delivers strategic insights to leadership, manages junior analysts, develops dashboards, and improves data quality across company platforms. The role requires translating quantitative findings for nontechnical audiences and applying healthcare or pharmaceutical dataset experience to strategic decision-making.

Conduct quantitative research for traders by testing market hypotheses, building and maintaining documented signals, performing event studies and backtests, and validating results against leakage, survivorship bias, transaction costs, and regime dependence. Organize reproducible point-in-time datasets, communicate findings clearly, track signal performance, and use AI tools to accelerate research and coding while verifying outputs.

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.