Top Data & Analytics Jobs in Detroit, MI

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

Lead company-wide data governance and standards, enforce data contracts and schema/version control, manage PII/RBAC and master data, establish data-quality metrics and monitoring, grow and run the governance team, remain hands-on with data profiling and SQL, and use AI to accelerate governance work and modeling.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

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.

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.

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 Technical Analyst will manage data workflows, ensure high-quality civic data acquisition, and enhance processes through technical leadership and collaboration with teams.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.