Top Senior Data & Analytics Jobs in Madison, WI

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

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.

Designs, builds, and supports scalable batch and streaming data pipelines, integration solutions, data models, APIs, and enterprise data platforms. The role focuses on cloud data architecture, data quality, governance, platform performance, and graph capabilities using Neo4j. It partners with stakeholders, analytics, and data science teams to support operational insights, AI, machine learning, fraud detection, and connected-data use cases.

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Leads complex business analysis, data reporting, ERP optimization, requirements gathering, system design, Workday configuration, testing, release implementation, process mapping, and end-user support. Serves as a strategic ERP advisor, recommends technology solutions, develops reports and documentation, resolves system issues, identifies training needs, and mentors junior staff across Finance, HR, and Research Administration systems.

Design, build, and maintain scalable data pipelines, ETL/ELT processes, enterprise data platforms, data models, and integrations. Ensure data quality, governance, security, performance, and reliability while supporting analytics, reporting, and business intelligence. Collaborate with stakeholders and technical teams to translate business needs into data solutions, modernize platforms, automate processes, and evaluate emerging technologies.

Lead the design, development, scaling, and operation of enterprise data platforms, services, and pipelines. Own mission-critical systems, deliver complex multi-team projects, build analytics solutions, and improve data delivery processes. Partner with architects, engineers, analysts, data scientists, and business stakeholders to create reliable, observable, secure, and governed platforms. Provide technical leadership, evaluate technologies, establish engineering best practices, mentor engineers, and guide technical decisions across teams.