Top Data & Analytics Jobs in Madison, WI

The Data Engineer will enhance the Enterprise Data Warehouse, modernizing ETL processes, optimizing data transformations, ensuring data quality, and providing production support while collaborating with cross-functional teams.

Design and enhance data management and analytics functions, build data assets, establish engineering standards, and enable self-service data access for analytics at Danaher.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

Manage leased partner network data integration into I-Network, ensure data quality and delivery for client claims systems and regulatory filing, support SFTP access, create requirements and QA sign-off for projects, produce analytical insights, mentor team members, and assist Business Development/National Accounts and project management.

Lead design and implementation of complex cloud-based data solutions on AWS. Define strategic roadmaps, advise pre-sales, interview and mentor architects/engineers, and oversee data standards, governance, and operational practices.

Lead and manage a team to define and execute business intelligence strategies, drive analytics initiatives, and ensure data quality and governance within a healthcare context.

Support client-facing performance measurement and reporting: calculate and validate outcomes, maintain dashboards and metrics, automate repeatable workflows, improve metric governance, and translate results into clear insights for internal and external stakeholders.

Lead centralization of performance data, define KPI standards, build scalable data infrastructure and executive dashboards (Looker), deliver cross-functional performance insights, forecasting, and predictive models to drive margin, LTV, and capital allocation decisions.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Implement and deliver Microsoft-based data solutions: gather requirements, build ETL pipelines, perform dimensional modeling, develop complex transformations (SQL, Python, DAX), and create Power BI reports while mentoring teammates and supporting client engagements.