Top Data & Analytics Jobs in Detroit, MI

Lead design and ownership of analytical frameworks and cross-functional reporting for finance and operations. Translate leadership goals into structured analytics projects, standardize metrics and reporting, build business cases, deliver executive-level narratives, and develop predictive models and dashboards to inform strategic decisions across insurance operations.

Deliver sales reporting, data preparation, dashboard updates, and analysis to support sales intelligence. Maintain data accuracy across the warehouse and CRM, build Power BI visuals, execute ETL processes, and translate insights for non-technical stakeholders.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

Lead product analytics for a B2B SaaS product: define metrics and measurement frameworks, analyze user behavior and product performance, build self-service dashboards, partner cross-functionally to link usage to business outcomes, and translate data into strategic recommendations for product roadmap and GTM decisions.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.