Top Data & Analytics Jobs in Madison, WI

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

Develop and maintain Epic Healthy Planet registries and analytics solutions: gather requirements, profile Epic source data, build rules/metrics/dashboards, provide ad-hoc analysis, support end users, document solutions, and mentor users.

Own revenue metrics, reporting, and deep-dive analyses to optimize sales and marketing performance. Build complex financial and operational models, automate data enrichment and workflows, audit commissions and funnels for data integrity, and partner with stakeholders to drive data-informed GTM decisions and expansion.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.

Partner with Product leadership to build scalable Snowflake data models, run behavioral and funnel analyses, design A/B tests and predictive models, and translate insights to influence roadmap and product strategy.

Lead development of provider data products and ML-based decision support, manage provider data quality, collaborate across teams to build provider-facing analytics, and establish MLOps standards and governance.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

Build and maintain Salesforce reports/dashboards, analyze marketing and funnel performance, partner with Marketing/RevOps, experiment with AI-driven data/enrichment workflows, ensure data quality across systems, and present insights to leadership.

Lead the data organization to define data strategy, build scalable cloud-native pipelines, enable self-service analytics, drive AI/ML initiatives, and manage a multidisciplinary team to inform product, clinical, and business decisions.