Senior Manager, Data Management

Senior Manager, Data Management

Ball Corporation

Westminster, CO, US, 80021

IT Administration

49222

The Senior Manager, Data Management leads the enterprise Data Management function encompassing Master Data Management (MDM), Data Quality, and Data Governance operations. This role is the enterprise accountability layer for data trust — owning the stewardship model, governance controls, data quality standards, and data security policy design that ensure enterprise data is accurate, defined, classified, and reliably governed.

• Data Governance COE:
  • Define and operate the enterprise data stewardship and ownership model — ensuring every critical data domain has a named business owner and active steward
  • Maintain the business glossary, enterprise data definitions, and ownership registry as living, governed artifacts — not static documentation
  • Run governance forums, decision rights frameworks, and escalation paths — resolving data definition disputes, ownership conflicts, and cross-domain data issues
  • Own data classification taxonomy and access policy design — defining RBAC policy tiers aligned to data sensitivity and regulatory requirements (policy design only; technical implementation owned by Data Platforms)
  • Own business metadata completeness and definition quality in the enterprise catalog (Microsoft Purview / Unity Catalog), ensuring Gold-layer assets are documented to enterprise standards
  • Serve as the policy interface to enterprise Info Sec for compliance validation, audit readiness, and regulatory data controls — operating as the data-side partner in incident response and access reviews
• Master Data Operations:
  • Oversee master and reference data workflows across SAP S/4
    
    HANA and JD Edwards — governing the creation, change, and maintenance processes for Customer, Product, Supplier, Site, and Cost Center master data
  • Accountable for accuracy and timeliness of master data — owning MDM SLAs as measurable commitments, not targets
  • Own preventive controls at data creation points — ensuring governance rules are embedded in the data request and approval workflow before bad data enters the system
  • Drive reduction of downstream rework caused by MDM defects — quantifying the operational and financial impact of master data failures and reporting improvement to the CDO and business leaders
  • Manage MDM release cycles, change control, and SLAs — coordinating MDM updates across SAP and JDE in alignment with ERP release schedules and Data Architecture standards
• Data Quality:
  • Define and own enterprise data quality rules and acceptance criteria — establishing the quality standards that analytics products and downstream systems must meet before data is certified for use
  • Produce enterprise DQ scorecards and trend reporting — publishing domain-level quality scores, issue aging, and improvement trajectories to the CDO and business data owners on a recurring cadence
  • Operate systemic escalation for recurring quality issues — routing persistent DQ failures to data owners, engineering teams, or MDM operations with clear accountability and resolution timelines
  • Accountable for measurable improvement in critical data domains — quality improvement targets are defined at the start of each year and tracked as a performance commitment

• Bachelor's degree required in Information Systems, Business Analytics, Computer Science, Business Administration, or related field preferred.
• Master's degree in a quantitative or information management discipline preferred.
• 8+ years in data management, data governance, or MDM roles within large enterprise environments
• 3+ years leading teams — direct or matrixed — with accountability for governance, quality, or MDM outcomes
• Experience operating data governance frameworks at enterprise scale: stewardship models, ownership registries, governance forums, and escalation processes
• Hands‑on experience with MDM platforms and ERP master data processes — SAP S/4
  
  HANA strongly preferred; JD Edwards a differentiator
• Familiarity with data quality tooling, scorecard development, and DQ rule design across critical data domains
• Experienc…