Top Analysis Reporting Jobs in Madison, WI

The Competitive Intelligence Manager transforms market data into actionable insights, conducts strategic analyses, develops sales tools, and collaborates with product management to influence roadmaps for competitive features.

As a Data Engineer, you will build and maintain data ingestion pipelines, develop data transformations, and migrate SQL Server processes to Azure-native solutions, supporting marketing campaigns and analytics teams.

Lead the architecture of the Workday Adaptive Planning platform, designing models, integrating systems, and ensuring platform governance while collaborating with stakeholders and optimizing performance.

The Manager, Analytics will lead B2B analytics efforts, overseeing reporting, data analysis, and collaboration with account teams to drive insights and performance improvements.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

Design, implement, and analyze randomized and quantitative social science studies for progressive organizations. Manage project lifecycle from scoping and survey/randomization design to analysis, reporting, and stakeholder communication. Maintain research partnerships, translate findings into actionable recommendations with an equity lens, and collaborate on team research strategy and new study ideas.

Lead market and client-level fundraising data analysis and publish original research and benchmarks. Partner with Sales, Customer Success, and Marketing to produce ROI cases, client insights, and thought leadership. Present findings publicly at conferences, build repeatable insight frameworks and tools, and translate data into persuasive narratives for advancement leaders.

Own and build reliable analytics data products: define metrics, create and maintain dbt models, design dashboards for growth/finance/ops, improve data quality via testing and monitoring, and enable self-serve analytics for stakeholders.

Design, build, and maintain Databricks-based data pipelines and ETL/ELT processes using Python and SQL. Optimize workflows for performance and cost, support data modeling and cloud integrations (Azure/AWS/GCP), monitor and troubleshoot pipelines, document best practices, and collaborate with cross-functional teams.

Design, build, and maintain scalable data pipelines and models; collaborate with analysts and data scientists to provision prepared datasets; implement data quality, governance and monitoring; recommend technologies; lead root-cause analysis, code reviews and testing; mentor teammates and support production data environments.