Top Analysis Reporting Jobs in Minneapolis, MN

Builds and maintains global Workday HR reporting infrastructure: gathers requirements, develops custom reports and dashboards, tests and validates solutions, supports UAT, mentors peers, handles ad-hoc data requests, and improves report performance and user adoption across HR teams.

Design, develop, and maintain enterprise data pipelines and data warehouse/BI solutions. Mentor junior engineers, define engineering standards, support DevOps/CI-CD practices, engage vendors, and participate in recruiting and product planning. Deliver scalable, resilient data solutions using cloud platforms and ETL tools.

Design, build, and maintain Power BI and Tableau dashboards; analyze large, complex datasets using SQL, Python, and statistical methods; partner with data engineering and business stakeholders to ensure data quality; translate findings into clear, actionable stories and executive-level presentations; support firmwide analytics growth and automation.

Design, build, and maintain scalable data pipelines and the enterprise data warehouse. Optimize schemas, implement ETL/ELT, manage cloud data infrastructure, enforce security/governance, and partner with BI and technology teams to ensure reliable, performant data for analytics.

Lead enterprise customer data governance and master data management. Define standards, golden records, data quality rules, and lineage. Partner cross-functionally to resolve data issues, ensure compliance, run SQL-based analyses, and drive change to enable data-driven decision making across global operations.

Monitor, measure, and improve enterprise data quality across sales, finance, supply chain, loyalty, and customer domains. Define and implement data quality rules, SLAs, and automated checks (Databricks/SQL/PySpark/Delta Lake). Perform data profiling, root-cause analysis, build scorecards/dashboards, support MDM and governance, and collaborate with Data Engineering, BI, and business stakeholders to drive continuous improvement.

Monitor, measure, and improve enterprise data quality across domains. Define and implement data quality rules, build automated checks in Databricks (Databricks SQL, PySpark, Delta Lake), perform data profiling and root cause analysis, create dashboards and scorecards, support governance and MDM, and collaborate with engineering and business stakeholders to drive continuous improvement.

Develop and productionize analytical models and data products to support underwriting and portfolio management. Apply statistical and machine learning methods to insurance datasets, perform exploratory analysis, feature engineering, validation, and create visualizations and presentations for technical and business stakeholders. Partner with underwriting, broking, actuarial, and portfolio teams to deliver scalable underwriting analytics and monitoring solutions.

Develop and productionize underwriting analytics, predictive models, and decision tools using statistical and machine learning techniques. Partner with underwriting, broking, actuarial, and portfolio teams to perform feature engineering, exploratory analysis, model validation, visualization, and monitoring to support risk segmentation, portfolio insights, and underwriting optimization.

The VP of Salesforce & Marketing Technology leads the strategy and execution of Salesforce and marketing technologies, ensuring integration and compliance to enhance customer engagement and business outcomes.