Top Analysis Reporting Jobs in Milwaukee, WI

The Principal Enterprise Data & Analytics Architect will design and modernize data architecture, guiding integration of cloud and on-premise solutions to enhance enterprise data management and analytics.

The Senior Systems Engineering Specialist will lead the deployment of a new PLM system, defining requirements, optimizing processes, and managing stakeholder engagement for effective system integration.

Build and operate reliable batch and streaming data pipelines from OT and enterprise systems into the UNS and analytics platforms. Integrate lab and shop-floor equipment and enterprise apps, implement CI/CD and IaC, enforce security and compliance (GxP/21 CFR Part 11), establish observability and runbooks, and collaborate with data science and stakeholders to define data contracts and reusable integration patterns.

This role oversees data-related risks ensuring compliance with enterprise standards, evaluates controls, develops risk processes, and leads governance efforts.

The role involves design and development using Markit EDM, analyzing code, preparing design documents, and implementing data integration projects.

As a Principal Statistical Programmer, you'll generate datasets, oversee CRO deliverables, support clinical reports, and ensure compliance with FDA regulations.

Develops and operationalizes data pipelines, engages with DevSecOps, and ensures data quality for analytics at Centene.

The role involves leading global forecasting and performance management, setting standards, overseeing processes, collaborating with cross-functional teams, and developing a high-performing team in the oncology biotech sector.

Lead the creation of analytics strategies, manage data pipelines and reporting solutions, and mentor data professionals while ensuring data usability and quality across the organization.

Build and operate scalable data pipelines and analytics-ready datasets using Python, dbt, and BigQuery. Develop Looker dashboards, ensure data quality and observability, optimize performance and cost, integrate data workflows with backend services and CI/CD, and support analytics, experimentation, and production use cases.