Top Data Management Jobs in Milwaukee, WI

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Lead development and implementation of data governance strategies, manage client accounts and deliverables, supervise and mentor teams, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements in data management processes.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Lead and grow a data platform engineering team to build and maintain a petabyte-scale data lake and infrastructure. Drive platform roadmap, scale systems globally, collaborate cross-functionally, and embed best practices for security, privacy, and AI transformation.

Lead and mentor a data engineering team building scalable customer-focused data solutions. Hands-on technical ownership, architecture guidance, and delivery of data ingestion, transformation, and reporting. Advance AI-enabled development practices, set technical standards, and foster a collaborative, accountable engineering culture to improve speed, quality, and reliability.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

Leads R&D data stewardship across metadata, cataloging, data products, profiling, quality, governance, and compliance. Uses Informatica, SQL, Databricks, Python, and PySpark to curate data, automate workflows, define quality controls, and resolve complex issues. Applies AI-assisted stewardship and semantic data concepts while collaborating with technical and business stakeholders. Coaches other stewards, supports audit readiness, and improves stewardship standards and operating practices.

Leads the architecture, implementation, and evolution of enterprise data platforms, including Master Data Management, data lakes, lakehouses, and cloud data services. Manages data engineers and developers, establishes engineering standards, oversees Azure-based integrations and pipelines, and owns data applications, databases, security, governance, and production support. The role also directs technical strategy, manages multiple initiatives, and communicates architecture and delivery plans to stakeholders.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Manage and improve corporate giving data systems: build and maintain Tableau/Excel dashboards, respond to ad hoc data requests, clean and govern community data, administer Bonterra/CyberGrants, and lead project management for giving programs and strategic initiatives while partnering with enterprise stakeholders.

Leads enterprise business intelligence and analytics strategy, owning the vision, roadmap, KPIs, and adoption measures for insight products. Manages data engineering and analytics teams, partners with senior leaders, translates business questions into analytical solutions, and delivers executive-ready insights. Provides technical oversight for data models, pipelines, semantic layers, data quality, scalability, and metric standardization across transformation, sales, operations, sustainability, and other enterprise domains.

Develop statistical, machine learning, and deep learning models to measure the impact of pharmaceutical HCP, DTC, and Medical Affairs campaigns. Partner with internal and external clients, provide analytical insights and methodological guidance, consult with sales and market research teams, and coach an offshore analytics team. The role requires applying causal inference, healthcare and pharmaceutical data expertise, and clear communication of findings to clients and executives.

Design, build, and test SAP MDM repositories and logical data models. Configure MDM clients (Console, Data Manager, Import Manager, Syndication Manager), create import/syndication maps, workflows, web services, DB views, and INI files. Perform repository operations with CLIX, prepare unit tests, validate integrations with upstream/downstream systems, and coordinate with data providers and consumers.

Design, build and maintain SAP MDM repositories and logical data models. Create functional and technical specs, configure MDM clients (console, data/import/syndication managers), web services, CLIX server ops, import/syndication maps, workflows, matching rules, DB views and INI files. Perform unit testing, validation and liaison with data providers.

Implement and maintain SAP MDM repositories and mappings. Design functional/technical specs, configure MDM clients (Console, Data Manager, Import/Syndication Manager), create import/syndication maps, web services, DB views and INI configurations. Develop workflows, matching rules, validations, CLIX server ops, unit tests, and test interfaces with upstream/downstream systems. Collaborate with data providers and cross-functional teams.

Design, build, and validate SAP MDM repositories and logical data models. Create functional/technical specs, import and syndication maps, configure MDM clients and web services, perform repository/CLIX operations, implement workflows, matching rules, validations, and DB views, prepare unit tests, and collaborate with data providers and business stakeholders while leading and motivating the team.

Lead design and implementation of SAP MDM repositories and data models; configure MDM clients, import/syndication maps, workflows, web services and CLIX operations; develop and test integrations with upstream/downstream systems; produce technical specifications and unit tests; coordinate with data providers and stakeholders.

Design, build, and test SAP MDM repositories and logical data models. Configure MDM clients (Console, Data Manager, Import/Syndication Managers), create import/syndication maps, web services, workflows, matching rules, and DB views. Perform CLIX and server/repository operations, configure INI files, prepare unit tests, validate repositories, and coordinate with data providers and consumers.

Implement and maintain SAP MDM repositories and logical data models; produce functional and technical design specs; configure MDM clients, import/syndication maps, web services and INI files; perform CLIX and DB view operations; design workflows, matching rules and validations; prepare unit tests; validate repositories; test interfaces with upstream/downstream systems; liaise with data providers and lead the team.

Implement and configure SAP MDM repositories and clients; design functional/technical specs, import/syndication maps, workflows, web services, CLIX operations, DB views, and test interfaces between MDM and upstream/downstream systems.