Top Senior Data Management Jobs in Detroit, MI

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Lead development and implementation of data governance strategies, manage client accounts and deliverables, supervise and mentor teams, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements in data management processes.

Lead and grow a data platform engineering team to build and maintain a petabyte-scale data lake and infrastructure. Drive platform roadmap, scale systems globally, collaborate cross-functionally, and embed best practices for security, privacy, and AI transformation.

Lead and grow a data engineering team to build scalable, cloud-native multi-cloud Lakehouse data products using Databricks, Spark, Delta Lake and near real-time streaming. Drive migration from legacy systems, enable AI/ML and GenAI use cases, ensure observability, data governance, CI/CD, and collaborate with product, analytics, security and architecture teams to deliver customer and marketing data solutions.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Manage and improve corporate giving data systems: build and maintain Tableau/Excel dashboards, respond to ad hoc data requests, clean and govern community data, administer Bonterra/CyberGrants, and lead project management for giving programs and strategic initiatives while partnering with enterprise stakeholders.

Leads Ascent’s data practice, including DBAs, analysts, and engineers; owns the data roadmap, warehouse, Snowflake modeling, integrations, governance, reporting modernization, data quality, backup, retention, budget, and delivery standards. Partners with software teams, resolves complex data issues, supports customer-facing reporting, coaches staff, manages offshore teams, and introduces AI tools into development and delivery.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

Lead a remote analytics team to deliver dashboards, data products, and decision-support tools. Oversee project plans, stakeholder engagement, data platform modernization, ETL/automation, Tableau/Power BI deployments, statistical modeling, QA, metadata, and staff mentoring to support federal social service programs.

Develop and implement commercial data acquisition and governance frameworks. Govern data standards, policies, cataloging, quality, lineage, privacy, and compliance. Evaluate and onboard external data sources, negotiate vendor agreements, and manage third-party data relationships. Lead governance platform deployment, training, change management, KPI development, reporting, and continuous improvement while coordinating Commercial Operations, Analytics, IT, and external partners.

Lead development and operation of the enterprise Data & Analytics platform. Own roadmap, platform capabilities, CI/CD, automated provisioning, monitoring, governance, cost optimization, and incident management. Partner with engineering, architecture, security, and business teams, act as product owner for platform services, and manage a team of platform engineers to enable self-service, secure, and scalable data delivery.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Lead a team delivering actuarial statistical reporting, regulatory submissions, and analytics. Ensure compliance with bureau requirements, drive automated reporting and UAT for policy/claims systems (Guidewire, Solartis), partner with actuarial, technology, and vendors, and manage stakeholder/regulator interactions while mentoring staff and improving data governance and reporting processes.

Manages reporting and analytics operations, teams, workflows, critical business intelligence reports, and performance metrics. Leads data process improvements, requirements analysis, systems development, testing, reporting projects, and process re-engineering. Uses SQL, data warehouses, QlikView, Tableau, and related tools to support operational, financial, quality, compliance, and strategic decisions. Mentors staff, manages priorities, monitors risks, and partners with business leaders and clients.

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.

Lead solution/data architecture for end-to-end enterprise data warehouse implementations including data integration, ETL, data marts, reporting, cubes and MDM. Design architectures using frameworks (Zachman/TOGAF), guide implementation teams, and apply healthcare payer domain expertise. Work with Oracle/DB2/SQL Server and major ETL/BI tools to deliver large-scale reporting and analytics solutions.

Owns the end-to-end architecture, development, infrastructure, data pipelines, and Power BI reporting platform supporting data governance, informatics, analytics, auditing, and data quality. Leads and mentors a data engineering team, defines schemas and engineering standards, ensures security and HIPAA compliance, oversees testing and Agile delivery, manages stakeholder requirements, and remains hands-on with backend technologies, data models, Power BI, and DAX.

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

Lead a hands-on data engineering team to build and scale production data pipelines, datasets, and observability for alternative-data products. Drive architecture, data modeling, QA, and AI-ready dataset design while coaching engineers, partnering with product and research, and owning operational excellence across Databricks, Airflow, SQL, and PySpark.