Senior Manager, Data Management

Ball•Westminster, CO

4d•$115,000 - $164,300•Hybrid

About The Position

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.

Requirements

Bachelor's degree required in Information Systems, Business Analytics, Computer Science, Business Administration, or related field 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/4HANA strongly preferred; JD Edwards a differentiator
Familiarity with data quality tooling, scorecard development, and DQ rule design across critical data domains
Experience defining data classification frameworks and access policy design (RBAC policy, not technical implementation)
Strong stakeholder management across business and IT — able to drive accountability without direct authority
Manufacturing or industrial sector experience — familiarity with Customer, Product, Supplier, and Site master data complexity
Experience with Unity Catalog, Microsoft Purview, or equivalent metadata and catalog platforms
DMBOK or CDMP certification — signals structured data management methodology
Experience supporting Finance, Supply Chain, or Commercial data domains at an enterprise level
Background operating in a product-based or federated data operating model — able to work within a CDO org with defined role boundaries
Policy-Layer Leadership — Operates effectively at the governance and standards layer without owning technical enforcement; understands where their authority ends and platform ownership begins
Accountability Architecture — Skilled at building accountability frameworks and stewardship models that drive behavior through ownership and incentive, not bureaucracy
Governance Facilitation — Effective at running governance forums, decision rights processes, and escalation paths that resolve disputes and produce durable decisions
Executive Communication — Translates data governance concepts, quality metrics, and policy decisions into business value language for CIO, CFO, and functional leader audiences
Structural Ambiguity Tolerance — Comfortable establishing governance structure in maturing organizations; can operate without perfect tooling or complete data inventories while building toward the target state

Nice To Haves

Master's degree in a quantitative or information management discipline preferred.
JD Edwards a differentiator
DMBOK or CDMP certification — signals structured data management methodology

Responsibilities

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 InfoSec for compliance validation, audit readiness, and regulatory data controls — operating as the data-side partner in incident response and access reviews
Oversee master and reference data workflows across SAP S/4HANA 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
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