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Data Manager Jobs in Milwaukee, WI (NOW HIRING)

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed ...

IT Manager, Data & Analytics Posting Start Date: 3/19/26 Job Location (Short): Milwaukee, Wisconsin, USA, 53204-2941 | Chicago, Illinois, USA, 60631 Requisition ID: 35392 Onsite or Remote: Onsite ...

CLA is looking to hire a Manger of Data Science This role constructs complex solutions that integrate data wrangling, visualization, and advanced modeling techniques into a seamless workflow using ...

The Sr. Parts Manager, Data Centers owns the endtoend parts business for industrial standby and prime-power generator sets serving hyperscale, cloud, and enterprise data centers. This role ensures ...

The Sr. Parts Manager, Data Centers owns the endtoend parts business for industrial standby and prime-power generator sets serving hyperscale, cloud, and enterprise data centers. This role ensures ...

Data Architect

Racine, WI · On-site

$59.75 - $77/hr

Data ingestion, Data Management, Data Delivery, Data Consumption. Key Responsibilities Outcomes: 1. Architect, design and implement high performance large volume data integration, transformation ...

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Data Manager information

See Milwaukee, WI salary details

$30.5K

$95.7K

$169.5K

How much do data manager jobs pay per year?

As of Jul 31, 2026, the average yearly pay for data manager in Milwaukee, WI is $95,711.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $123,600.00 per year, depending on experience, location, and employer.

What is the salary of a data manager?

The salary of a data manager typically ranges from $70,000 to $120,000 annually, depending on experience, industry, and location. Professionals with advanced skills in database management, data analysis, and familiarity with tools like SQL or Python tend to earn higher salaries.

What is a Data Manager?

A Data Manager is a professional responsible for overseeing the collection, storage, organization, and safeguarding of data within an organization. They ensure that data is accurate, accessible, and secure, often working with databases and data management systems. Data Managers also develop data policies, maintain data quality, and support teams in using data effectively for decision-making. Their role is crucial in industries where large volumes of information are handled, such as healthcare, finance, and research.

What is the difference between Data Manager vs Data Analyst?

AspectData ManagerData Analyst
Required CredentialsBachelor's degree in IT, Computer Science, or related field; certifications like CDMP or DAMA often preferredBachelor's degree in Statistics, Mathematics, or related field; certifications like CAP or Microsoft Data Analyst are common
Work EnvironmentTypically manages data systems, databases, and teams; works in IT or data departmentsAnalyzes data sets, creates reports, and visualizations; often works in business or analytics teams
Employer & Industry UsageUsed across industries like healthcare, finance, and tech for data governance and managementCommon in marketing, finance, and consulting for insights and decision-making

While both roles involve working with data, Data Managers focus on overseeing data systems and ensuring data quality, whereas Data Analysts interpret data to generate insights. Understanding these differences helps in choosing the right career path or job search focus.

What Is a Data Manager?

A data manager is responsible for creating and managing databases that meet the specific needs of a company or organization. As a data manager, your job duties include assessing customer database requirements, modifying the structure of existing databases, and handling the backup and recovery of older systems. You should have experience working with many database system varieties and large volumes of customer records. You can find data manager positions in a wide range of industries.

What jobs pay 200,000 a year in the USA?

Data managers typically do not earn $200,000 annually unless they hold senior or specialized roles such as Director of Data or Chief Data Officer, which require extensive experience, advanced skills in data analysis and management tools, and often leadership responsibilities. High-paying roles in data management are usually found in large corporations or industries like finance, technology, and healthcare. Salary levels depend on experience, education, certifications, and the size of the organization.

What are the key skills and qualifications needed to thrive as a Data Manager, and why are they important?

To thrive as a Data Manager, you need expertise in data management principles, database administration, and data governance, often supported by a bachelor's degree in computer science or a related field. Familiarity with SQL, data warehousing tools, data visualization platforms, and certifications like CDMP or DAMA are typically required. Strong analytical thinking, attention to detail, and effective communication are essential soft skills for ensuring data integrity and collaborating with stakeholders. These skills and qualifications are crucial for maintaining secure, accurate data systems and supporting informed business decisions.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as data analysis, SQL, and visualization tools, along with continuous learning and certification if needed.

How does a Data Manager typically collaborate with other departments to ensure data integrity?

As a Data Manager, collaboration with various departments—such as IT, analytics, and operations—is essential to maintain data integrity and consistency. You’ll regularly coordinate with these teams to establish data governance protocols, resolve discrepancies, and ensure that data collection and storage meet organizational standards. Open communication and regular meetings help address data quality issues and align data management practices across the organization. This cross-functional work not only supports accurate reporting but also drives better decision-making company-wide.

What is the role of a data manager?

A data manager is responsible for overseeing the collection, storage, organization, and maintenance of data within an organization. They ensure data quality, security, and accessibility, often using database management tools and following data governance standards. Their role supports data analysis and decision-making processes.
What are the most commonly searched types of Data jobs in Milwaukee, WI? The most popular types of Data jobs in Milwaukee, WI are:
What cities near Milwaukee, WI are hiring for Data Manager jobs? Cities near Milwaukee, WI with the most Data Manager job openings:
Infographic showing various Data Manager job openings in Milwaukee, WI as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $95,711 per year, or $46 per hour.

Data Manager - AI Development

GE HealthCare

Waukesha, WI • On-site

Full-time

Re-posted 20 days ago


GE HealthCare rating

8.4

Company rating: 8.4 out of 10

Based on 137 frontline employees who took The Breakroom Quiz

99th of 487 rated machine equipment manufacturers


Job description

Job Summary:
GE HealthCare is a leader in healthcare innovation, and they are seeking a Data Manager for their AI Development team. This role is responsible for planning, coordinating, tracking, and governing data used to develop AI-enabled medical device features, working closely with AI/ML engineers and various stakeholders to ensure data readiness and compliance throughout the development lifecycle.
Responsibilities:
• AI Data Planning & Requirements
• Partner with AI/ML engineers and technical leads to define data requirements for AI features, including dataset scope, diversity, and usage intent.
• Translate feature and model needs into clear data requirements that guide collection, annotation, and preparation activities.
• Support creation and maintenance of AI data planning artifacts aligned with internal Quality Management System (QMS) requirements.
• Data Collection Coordination
• Coordinate with centralized and distributed data collection teams to support AI development needs.
• Track data sourcing activities across multiple programs and stakeholders.
• Maintain data collection dashboards that provide visibility into status, coverage, risks, and gaps.
• Track data collection and annotation budget.
• Annotation & Labeling Oversight
• Coordinate data annotation activities with internal teams and external vendors.
• Track annotation progress, throughput, and quality metrics.
• Maintain annotation dashboards to ensure timely delivery aligned with AI development milestones.
• Data Governance & Compliance Support
• Support execution of AI data management practices including:
• Data control planning
• Data segregation between training, holdout, and testing datasets
• Data preparation and inclusion criteria
• Data traceability and usage documentation
• Ensure datasets are properly documented and traceable to their original sources to support audits and regulatory submissions.
• Act as a point of coordination to ensure data activities align with applicable QMS work instructions for AI development.
• Program Tracking & Communication
• Serve as the central coordination point for AI data activities across engineering, data operations, and program teams.
• Proactively communicate status, risks, and dependencies to stakeholders.
• Support planning reviews, design reviews, and readiness discussions with accurate data status reporting.
Qualifications:
Required:
• Bachelor’s degree in Engineering, Computer Science, Data Science, Biomedical Engineering, or a related technical discipline with 4 years of experience.
• Experience in data management, data operations, or program coordination roles supporting technical or engineering teams.
• Demonstrated ability to plan, track, and coordinate complex workflows across multiple stakeholders.
• Strong written and verbal communication skills, with the ability to translate technical needs into actionable plans.
• Experience creating and maintaining dashboards (eg. PowerBI, excel, smartsheet) trackers, or reports for operational visibility.
• Familiarity with structured data workflows(eg. SQL), including data collection, annotation, and dataset organization(eg. Python).
• Ability to work effectively in cross‑functional teams within a regulated or quality‑driven environment.
Preferred:
• Experience supporting AI / machine learning development teams, particularly in healthcare or medical devices.
• Familiarity with AI data lifecycle concepts, including training, validation, and testing datasets.
• Knowledge of medical imaging data formats and annotation tools (e.g., V7).
• Exposure to regulated development environments (medical devices, healthcare software, or similar).
• Understanding of data governance concepts such as data traceability, segregation, and controlled usage.
• Experience coordinating external vendors or annotation partners.
• Comfort working with ambiguity and evolving requirements in early‑stage AI feature development.
• Experience with Microsoft Forms
Company:
GE Healthcare provides a wide range of medical technologies and services to healthcare providers and researchers. It is a sub-organization of General Electric. Founded in 1892, the company is headquartered in Chicago, USA, with a team of 10001+ employees. The company is currently Late Stage.

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