Top Senior Data & Analytics Jobs in Milwaukee, WI

Lead design, implementation, and optimization of cloud-native data platforms (Snowflake, AWS, Azure) for managed-services clients. Translate business requirements into secure, scalable architectures, drive migrations and performance tuning, and provide hands-on technical leadership. Collaborate with cross-functional teams, mentor junior engineers, and contribute to best-practice frameworks, automation, and pre-sales efforts.

Customer-facing specialist guiding enterprise cloud data engineering and lakehouse transformations. Architect and optimize large-scale data pipelines, perform performance and load testing, support pre-sales POCs and workload sizing, lead adoption workshops, and mentor peers to drive Databricks platform adoption.

Lead process mapping, analysis, and redesign to improve efficiency and outcomes. Partner with stakeholders to gather requirements, analyze data (SQL, Excel, Power BI), define KPIs, apply Lean/Six Sigma methods, and support automation and digital transformation initiatives to drive growth, profitability, and loss reduction.

Lead research and listening for a specific audience: design and run primary research, integrate listening signals, synthesize quantitative and qualitative insights, and deliver timely, decision-oriented recommendations while coaching analysts and partnering with enterprise stakeholders.

Manage and administer SQL Server, PostgreSQL, MySQL, and NoSQL platforms. Handle backups, archiving, security, performance tuning, ETL/SSIS and cloud data pipelines, and support reporting, DevOps, and application teams. Monitor jobs, troubleshoot issues, implement best practices, and drive automation and optimization across dev/staging/production environments.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.

Lead development and governance of the supply chain data warehouse and analytics platforms. Build SQL-driven models, dashboards, and KPIs to drive inventory optimization, cost reduction, supplier performance, and working capital improvements. Support ERP integrations and data migrations, perform deep data discovery and predictive analytics, and present actionable insights to senior leaders to enable strategic decision-making.

Lead technical data exchange and onboarding for client file feeds, own inbound data quality and acceptance criteria, detect and resolve quality degradation, document integrations and specs, coordinate with engineering/product/analytics and client teams, and drive standardization and process improvements to ensure timely, spec-compliant file exchanges and SLA adherence.

Builds and maintains analytical data foundations for lending, underwriting, pricing, originations, collections, and portfolio analytics. Develops reusable SQL assets, dimensional models, data marts, transformation workflows, reporting solutions, and business intelligence products using SQL, Python, dbt, Git, Snowflake, Power BI, and Sigma. Partners with technical teams, analysts, and business stakeholders to integrate data, standardize metrics, automate testing, and deliver reliable, documented, scalable analytical assets.

Embed with a core business area to define problems, build reports and experiments, analyze data, surface insights, and drive high-impact recommendations end-to-end across growth, product, AI, or partnerships.