Director, Master Data Strategy & Governance

Ferrara•Chicago, IL

12d•$141,216 - $197,702•Hybrid

About The Position

Reporting directly to the VP, Data, Analytics & AI, the Director, Data and AI is a strategic change leader responsible for defining governance frameworks and driving organizational adoption across master data, data products, and AI tools. This pivotal role establishes and leads the enterprise’s integrated governance and adoption strategy, ensuring our most critical data assets—customers, products, vendors, and materials—are governed consistently and leveraged effectively across all business systems. The Director will architect and operationalize governance approaches for master data (SAP S/4HANA, commercial platforms, supply chain systems), data products (Databricks), and AI tools (Claude, Microsoft Copilot), while mobilizing the organization to embrace these capabilities. This leader will work cross-functionally to stand up governance processes, accountability structures, and adoption mechanisms that embed data and AI into decision-making and drive operational excellence. Successful candidates will have demonstrated success building MDM and data management capabilities in complex, multi-ERP environments and will bring the business acumen to align data strategy with enterprise objectives. A background in CPG, food & beverage, or consumer goods is strongly preferred. The scope spans master data governance, enterprise data integration, data quality, analytics enablement, and AI/ML strategy across our ERP landscape (SAP S/4HANA), commercial platforms, supply chain systems, Databricks, and downstream analytics environments. This leader works closely with the CIO, IT leadership, VP of Analytics, and cross-functional business partners to build a high-integrity, AI-ready data environment that enables analytics, machine learning, and operational excellence.

Requirements

Advanced proficiency with SAP MDG and SAP S/4HANA master data architecture
Hands-on experience with enterprise MDM platforms and data governance tools
Strong command of data governance frameworks (DAMA-DMBOK, DCAM) and data quality methodologies
Demonstrated ability to build and develop high-performing teams
Strong ability to influence cross-functional stakeholders at all levels
Proven change management and organizational transformation experience
Excellent communicator with strong executive presence
Bachelor’s degree required
15 years of progressive experience in data management with at least 5 years in a senior leadership role for enterprise MDM or data governance
Demonstrated success building MDM capabilities in complex, multi-ERP environments
Strong proficiency with cloud data platforms
Hands-on expertise with SAP MDG, SAP S/4HANA master data objects, and at least one enterprise MDM platform
5+ years in a people leadership role with team hiring and development
Exposure to AI/ML tools and workflows

Nice To Haves

Master’s degree in Data Management, Computer Science, Information Systems, Business Administration, or related field preferred.
Experience in CPG, food & beverage, retail, or similarly complex, high-SKU-count industries
Proven success governing master data through ERP consolidations or SAP S/4HANA migrations
Experience building or scaling data analytics centers of excellence
Track record in developing and launching AI pilots or enterprise AI governance frameworks
Certifications: CDMP, DAMA, SAP MDG, or cloud platform certifications
Experience with Databricks, particularly in governance and data quality

Responsibilities

Define and govern data architecture standards and decisions for scalability, reliability, performance, and cost optimization across on-premise and cloud environments, ensuring enterprise alignment
Collaborate with IT applications and support integration teams to ensure consistent master data flows across ERP, CRM, WMS, and analytics platforms
Establish data lineage, documentation, and discoverability standards across the enterprise
Ensure compliance with data privacy and retention regulations (GDPR, CCPA, HIPAA, SOX where applicable)
Define and operationalize data quality KPIs, including accuracy, completeness, consistency, and timeliness metrics across all master data domains.
Implement automated data quality monitoring, cleansing workflows, and enrichment processes to maintain high-integrity datasets.
Drive root cause analysis on systemic data quality issues and implement sustainable corrective action programs.
Establish a single source of truth for critical master data entities, reducing duplication and ambiguity across business systems.
Define and execute a flexible, pragmatic AI governance strategy and adoption roadmap that drives responsible use of diverse AI tools—Claude (for research and analysis), Microsoft Copilot (for productivity), Databricks Genie (for analytics automation)—across the organization
Establish governance practices that support AI/ML initiatives, including model training, inference, and deployment
Partner with data science and analytics teams to deliver well-governed, high-quality data products that accelerate business intelligence
Champion AI literacy and responsible AI adoption across the organization by establishing governance guardrails, training programs, and best practices that enable enterprise-wide capability building
Foster a data-driven, AI-ready culture by championing best practices
Define and execute the enterprise Master Data Management strategy, roadmap, and operating model in alignment with IT and business strategy
Establish governance frameworks, data ownership accountability, and stewardship processes for all master data domains (product, customer, vendor, material, finance)
Lead the MDM Center of Excellence, setting standards, policies, and processes for data definition, creation, maintenance, and archiving
Own the SAP MDG platform, including data model, governance workflows, BRF+ rules, change request configuration, and integration with SAP S/4HANA
Lead implementation, enterprise adoption, and execution of the SAP MDG roadmap
Govern master data processes during M&A integrations, ERP migrations, and other transformation initiatives
Define comprehensive governance approaches and frameworks for master data, data products, and AI tools that establish clear decision rights, accountability models, and operational standards across the enterprise
Stand up governance processes and operational mechanisms that institutionalize master data quality, data product stewardship, and responsible AI practices across business units and functions