Top Data Management Jobs in Milwaukee, WI

Leads and develops a team of Conversion Data Analysts, owning workload prioritization, delivery quality, and performance outcomes. Uses KPIs and data to identify risks, guide decisions, and improve high-volume conversion workflows. Partners with project management, Engineering, Product, Support, and leadership to ensure accurate data mapping and successful customer onboarding. Requires people leadership, SQL, Excel, data validation, CRM, and conversion tooling experience.

Manages the enterprise Data Governance and Analytics Center of Excellence, leading staff, governance initiatives, analytics strategy, maturity modeling, budgets, vendors, and planning. Coordinates data quality, stewardship, privacy, acquisition, and release programs while partnering with data scientists, engineers, technology governance teams, and business stakeholders. Develops executive presentations, aligns enterprise definitions and algorithms, establishes standards, and ensures analytics projects and business cases meet organizational objectives and deadlines.

Leads data strategy and analytics for the Risk/Credit team, translating complex datasets into insights for Credit, Operations, Marketing, Product, and Finance. Responsibilities include automating Python/R workflows, building Tableau dashboards, partnering with Data Engineering on Databricks workflows, conducting strategic analyses, monitoring data quality, presenting recommendations to leadership, and documenting analytical methodologies. The role requires strong SQL, cloud data warehouse, visualization, analytics programming, distributed computing, and version-control expertise.

Own end-to-end analytics delivery for a client POD, translating business priorities into workplans, coordinating cross-functional teams, governing delivery and revenue KPIs, and managing risks through resolution. Perform hands-on data profiling, validation, reconciliation, exploratory analysis, automation, and quality reviews using SQL, Python, Databricks, and Excel. Create executive-ready KPI, revenue, and business-impact narratives, prioritize initiatives, support business cases, and identify opportunities for analytics automation and AI-enabled improvements.

Lead design and build of a cloud-based data platform; manage and mentor data engineering staff; define engineering standards, data governance, and access controls; partner with stakeholders to deliver scalable, reliable data pipelines and platform services for analytics and AI.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.

Manage and mentor a data engineering team while leading Snowflake-based platform architecture, enterprise data integrations, governance, observability, and pipeline reliability. Partner with analysts, business leaders, product management, and engineering teams to improve trusted self-service data access. Establish engineering standards, modernize the data stack, optimize costs, and deliver an AI-ready data foundation supporting analytics, reporting, and future AI initiatives.

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.

Own the strategy, governance, architecture, modeling, and reporting foundation for People Experience data. Build governed metrics, semantic and consolidated data layers, dashboards, data catalogs, quality monitoring, and operating processes from the ground up. Manage intake, prioritization, access, privacy, enablement, and self-service adoption while partnering with stakeholders on analytics and future AI capabilities. The role combines strategic program leadership with hands-on SQL, data modeling, reporting, and team mentoring.

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.

Lead architecture and operations for the end-to-end data lifecycle: pipeline orchestration, dbt projects, cloud warehouse performance, dimensional modeling, data observability, HIPAA controls, and platform governance. Mentor a distributed data engineering team, partner with Analytics and Finance, and prioritize durable platform capabilities that enable BI, experimentation, and AI use cases.

Lead and scale the enterprise data hub: manage the data warehouse, build reliable ingestion and transformation pipelines, implement governance and data modeling best practices, deliver GTM-ready metrics, enable AI/ML use cases, prioritize the data roadmap, and lead/mentor a data engineering team.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.