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Data Management Jobs in Madison, WI (NOW HIRING)

Partner with investigators to develop and implement data management and sharing plans for grant applications, ensuring alignment with funding agency requirements and FAIR (Findable, Accessible ...

Data Engineer (Hybrid)

Cottage Grove, WI · On-site

$108K - $130K/yr

Design, build, and maintain data architectures, databases, data models, and integration solutions that enable scalable and reliable data management. * Partner with business leaders, developers ...

General Data Management Play a critical role in architecting our data and analytics solution landscape. Demonstrate competence, experience, knowledge, understanding, and advocacy of data management ...

Lead the planning, deployment, and ongoing management of data engineering initiatives and related projects. * Evaluate and prioritize data engineering work based on firm needs, strategic value, and ...

New

Streamline and standardize reporting processes to ensure timely, accurate delivery of key metrics Data Management & Quality * Partner with the Data Engineering team to source, integrate, and validate ...

New

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Showing results 1-20

Data Management information

See Madison, WI salary details

$31.2K

$97.9K

$173.3K

How much do data management jobs pay per year?

As of Jul 27, 2026, the average yearly pay for data management in Madison, WI is $97,900.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,500.00 and $126,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Data Management professionals in ensuring data quality and consistency across departments?

Data Management professionals often encounter challenges such as inconsistent data entry practices, siloed information systems, and varying data standards across departments. Addressing these issues typically involves implementing data governance frameworks, standardizing processes, and fostering collaboration between teams to ensure data integrity. Regular audits, cross-functional meetings, and the use of data quality tools are common strategies employed to maintain high standards and support organizational decision-making.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst, as the role values skills such as data analysis, programming, and statistical knowledge, which can be acquired through training or certification regardless of age. Many professionals successfully transition into data analysis later in their careers by gaining relevant skills and experience.

What Is a Data Management Analyst?

A data management analyst is responsible for maintaining databases. In this position, your responsibilities are to keep an eye on how secure the data is and look for ways to increase user efficiency when accessing it. For example, you might move the database to an online cloud-based server to free up system resources. A data management analyst has to have a solid grasp of network technology, in addition to familiarity with database and spreadsheet software, to perform the duties of the job.

Is data management a good skill?

Data management is a valuable skill for data management professionals, as it involves organizing, storing, and maintaining data to ensure accuracy and accessibility. Proficiency with database tools, data governance, and data quality standards enhances job performance and career prospects in this field.

What are the key skills and qualifications needed to thrive in Data Management, and why are they important?

To excel in Data Management, you need a strong background in data analysis, database design, and data governance, often supported by a degree in computer science or information systems. Familiarity with database management systems (like SQL, Oracle), data visualization tools, and certifications such as Certified Data Management Professional (CDMP) are highly valued. Attention to detail, problem-solving, and strong organizational skills help professionals ensure data integrity and facilitate effective collaboration. These competencies are crucial for maintaining accurate, secure, and accessible data, which underpins informed business decision-making.

What skills are needed for data management jobs?

Data management jobs require strong analytical skills, proficiency in database tools like SQL and Excel, and knowledge of data governance and security practices. Attention to detail, problem-solving abilities, and familiarity with data modeling and cleaning are also important. Certifications such as Certified Data Management Professional (CDMP) can enhance qualifications.

What is data management as a job?

Data management as a job involves organizing, storing, and maintaining data to ensure its accuracy, security, and accessibility. Professionals in this field often work with database systems, data governance, and data quality tools, requiring skills in SQL, data modeling, and sometimes certifications like CDMP or DAMA-DMBOK. The role supports organizations in making informed decisions and complying with data regulations.

What is data management?

Data management is the process of collecting, storing, organizing, and maintaining data in a secure and efficient manner. It ensures that data is accurate, available, and accessible to authorized users when needed. Good data management practices help organizations make informed decisions, comply with regulations, and protect sensitive information. It often involves the use of specialized software, policies, and procedures to handle data throughout its lifecycle.

What is the difference between Data Management vs Data Analyst?

AspectData ManagementData Analyst
Primary FocusOrganizing, storing, and maintaining data integrityAnalyzing data to extract insights and support decision-making
Skills & CertificationsDatabase management, SQL, data governance certificationsStatistical analysis, Excel, data visualization tools
Work EnvironmentData warehouses, IT departments, enterprise systemsBusiness units, analytics teams, consulting firms
Industry UsageUsed across industries for data infrastructureUsed for reporting, forecasting, and strategic analysis

While Data Management focuses on maintaining and organizing data infrastructure, Data Analysts interpret this data to generate insights. Both roles are essential for effective data-driven decision-making but serve different functions within an organization.

What are the most commonly searched types of Data Management jobs in Madison, WI? The most popular types of Data Management jobs in Madison, WI are:
What are popular job titles related to Data Management jobs in Madison, WI? For Data Management jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Data Management jobs in Madison, WI look for? The top searched job categories for Data Management jobs in Madison, WI are:
What cities near Madison, WI are hiring for Data Management jobs? Cities near Madison, WI with the most Data Management job openings:
Infographic showing various Data Management job openings in Madison, 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 $97,900 per year, or $47.1 per hour.
Lead, Master Data Management

Lead, Master Data Management

Springs Window Fashions

Middleton, WI • On-site

Full-time

Posted 21 days ago


Springs Window Fashions rating

6.7

Company rating: 6.7 out of 10

Based on 8 frontline employees who took The Breakroom Quiz


Job description

Job Summary:
Springs Window Fashions is North America’s premier window covering company, dedicated to creating the Best Experience for all stakeholders. The Lead, Master Data Management will oversee enterprise MDM initiatives, balancing technical execution with functional leadership to design and enhance scalable master data solutions across business processes.
Responsibilities:
• Serve as a functional lead on MDM initiatives, guiding solution design, process definition, stewardship practices, and alignment with MDM standards and governance expectations.
• Mentor and guide MDM Application Developers, MDM Analysts, and business data stewards, supporting skill development, knowledge sharing, and best practice adoption.
• Partner with business stakeholders, Data Engineering, BI & Analytics, Financial Systems, and other IT counterparts to translate master data needs into scalable, governed solutions.
• Coordinate cross-functional MDM workstreams, helping prioritize issues, resolve data and process challenges, and maintain continuity across systems and domains.
• Serve as a backup to the Manager, Master Data Management, or as the primary MDM functional lead when needed, supporting stakeholder engagement, initiative leadership, and MDM delivery continuity.
• Design, develop, and enhance master data solutions, workflows, data models, hierarchies, validation rules, and supporting processes across key enterprise data domains.
• Support the evaluation, selection, and implementation of MDM platforms and tools to enable scalable and sustainable master data management capabilities.
• Ensure MDM solutions support multiple data domains, including customer, product, vendor, financial, and other critical enterprise data.
• Provide technical leadership in defining data models, hierarchies, solution workflows, and supporting structures that enable efficient, governed master data management.
• Collaborate with Data Engineering & Architecture teams to align MDM solutions with enterprise data platforms, integration patterns, and downstream analytics needs.
• Support the definition and adoption of master data standards, ownership models, stewardship workflows, and lifecycle management processes.
• Partner with business data stewards to define data quality rules, validation logic, approval workflows, and maintenance processes.
• Develop and monitor data quality standards, controls, and metrics to improve master data accuracy and consistency.
• Drive root cause analysis and resolution of data quality issues across systems.
• Lead continuous improvement of master data processes, workflows, and controls.
• Collaborate with the Data Warehousing & Integration (DAWGs) team to ensure master data is consistently integrated across enterprise systems and analytics platforms.
• Partner with BI & Analytics teams to support trusted master data for reporting, dashboards, certified datasets, and decision-making.
• Work closely with Financial Systems, Pricing, ERP, and operational teams to align master data structures with business processes and system requirements.
• Support integration of multiple data sources and applications to enable reliable, consistent master data flows across enterprise platforms.
• Contribute to documentation of data flows, source-to-target mappings, data definitions, and integration patterns that support enterprise data consistency.
• Oversee support and drive improvement of MDM applications and processes, including issue resolution, enhancements, performance optimization, and workflow efficiency.
• Ensure appropriate testing and release management practices are followed for MDM solutions to support reliable delivery and operational continuity.
• Maintain documentation of MDM processes, solution designs, data structures, standards, and support procedures to enable knowledge transfer and consistent execution.
• Track solution effectiveness and identify opportunities to mature MDM capabilities toward governed, decentralized maintenance, improved data quality, and scalable stewardship.
Qualifications:
Required:
• 4+ years of progressive experience in master data management, data governance, enterprise application development, or related enterprise data roles.
• Bachelor’s degree in Computer Science, Information Technology, Information Systems, Data Management, Data Science, Business Analytics, or a related field required.
• Professional certifications in data management, data governance, MDM platforms, business analysis, cloud platforms, or related technologies (e.g., Informatica, Microsoft Azure, AWS, or similar) are highly valued.
• Experience translating business requirements into scalable technical solutions, data processes, workflows, validation rules, and data quality controls.
• Experience designing, developing, supporting, or improving master data solutions, data models, workflows, or enterprise data applications.
• Demonstrated commitment to ongoing professional development through training, certifications, conferences, and industry engagement.
• Strong proficiency in SQL and relational database concepts, with experience working with complex, multi-source datasets.
• Familiarity with data governance practices, data quality management, stewardship workflows, and master data lifecycle processes.
• Demonstrated ability to analyze complex data and process issues, perform root cause analysis, and develop practical solutions that improve data accuracy and reliability.
• Experience collaborating across business and technical teams to deliver data-driven solutions aligned with operational, financial, analytical, or enterprise system needs.
• Ability to provide guidance, influence stakeholders, and support alignment across cross-functional teams without relying solely on formal authority.
• Strong communication skills with the ability to explain technical and data concepts to technical and non-technical stakeholders.
Preferred:
• Contribution to MDM or data governance initiatives in an enterprise environment.
• Familiarity with MDM platforms or tools such as Informatica MDM, Reltio, Profisee, SAP MDG, Microsoft-based solutions, or similar technologies.
• Working knowledge of multiple master data domains such as customer, product, vendor, financial, location, or organizational data.
• Background supporting ERP, financial systems, pricing systems, product configuration, or other complex enterprise data structures.
• Exposure to manufacturing, consumer products, or similarly complex environments with configurable products, multi-system data flows, or distributed data ownership.
• Demonstrated ability to mentor technical or business team members, lead workstreams, or act as a lead contributor on data-related initiatives.
Company:
Springs Window Fashions supplies leading retailers and distributors with a complete line of blinds, shades, specialty treatments. Founded in 1939, the company is headquartered in Middleton, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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