Top Senior Data & Analytics Jobs in Milwaukee, WI

Design, build, and maintain scalable ETL/ELT data pipelines and analytical platforms on AWS and Databricks. Migrate legacy workflows to cloud-native services, implement data lake and catalog solutions, enable AI/RAG/vector search, ensure FedRAMP/NIST compliance, optimize performance, and mentor junior engineers while collaborating in Agile teams.

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 analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

Lead client-facing Collibra implementations across data governance, metadata management, catalogs, glossaries, workflows, and stewardship. Facilitate discovery and design workshops, translate requirements into scalable Collibra designs, configure and develop platform capabilities, drive integrations and testing, and coach client teams for adoption and sustainment.

The Business Intelligence / Data Analyst will optimize the data reporting pipeline using Google Big Query and Omni, work with product management, implement reports, and conduct ongoing maintenance.

The Sr. FWA Analyst identifies fraud, waste, and abuse in medical billing through data analysis, supporting engineering and data science teams with validation and tuning of detection algorithms.

Design and deliver Databricks-centric data architectures, lead pre-sales and billable engagements, build end-to-end data engineering pipelines for AI/ML and BI, mentor teams, ensure data governance/security/quality, and resolve data system issues while producing solution documentation and presentations.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.