Senior Manager, Procurement Data Excellence & Governance

What You'll Do

• A core expectation is to move procurement’s data function from reactive clean-up to an agent-embedded, self-improving operating model — where governance is executable, quality is measurable, and business value is demonstrable.
• Data Governance & Quality Operations Own the procurement data governance framework — policies, standards, decision rights, and the data stewardship operating model — and ensure it is applied consistently across systems and regions.
• Lead data quality and master data operations (Vendor Master, Material Master, spend, category taxonomy), moving from recurring manual clean-up toward monitored, controlled, and preventable quality at the source.
• Shift governance from static documents to executable rules — champion lightweight, machine-readable policies and standards that agents can enforce automatically.
• Align data handling with enterprise controls — sensitivity labels, data loss prevention, and approved access — so data can be used safely by both people and AI agents.
• Business Value & Performance Measurement Own Global Procurement KPIs, metrics, and program reporting — providing leaders with a single, trusted source for performance and value.
• Lead the labor productivity and business value agenda: define, quantify, and report the value realized from transformation, automation, and AI initiatives.
• Establish data quality KPIs, service level agreements, and monitoring so quality and value are managed with evidence, not assumed.
• Procurement Data Strategy & AI Readiness Reimagine the data governance and excellence operating model with agents embedded — defining the target model, the agentic patterns that apply (data quality agent, lineage agent, maintenance agent, steward copilot), and a getting-started roadmap sequenced against ERP and transformation milestones.
• Set and drive the procurement data strategy, prioritizing the Critical Data Elements that carry the most downstream value.
• Partner with the AI Data Strategist and agent build leads to define the data elements, quality thresholds, and validation rules each agent needs — mapping every business requirement to a source, owner, and readiness action.
• Direct the design of the feedback loop between agent, source system, and steward so validation, correction, and prevention happen without manual clean-up wherever feasible.
• Data Lineage & Technical Foundations Direct the working-level technical foundations that make the agentic model possible — data lineage, relationships, schema, and cross-system mapping — so downstream impact is traceable before a change lands.
• Stand up and maintain a searchable data dictionary, business glossary, documentation, versioning, and change history that both people and agents can query and update.
• Define control points at the point of entry so quality is protected where data originates.
• Innovation & Reusable Assets Sponsor rapid experiments on agentic data patterns, validate impact, and turn the best into reusable building blocks for broader adoption across Source-to-Pay.
• Pilot AI-based data validation and cleansing tools and assess fit against Micron’s data landscape.
• Team Leadership, Enterprise Partnership & Change Lead, coach, and develop a multi-region team; build depth, ownership, and succession, and coach stewards, custodians, and business owners for an agent-embedded operating model.
• Partner with IT, Security, Compliance, and Data Excellence to align procurement’s data strategy with enterprise standards, ERP migration readiness, and approved connectors.
• Represent the data agenda in program reviews and executive readouts, and drive adoption through clear communication, enablement, and change management. ▍ Leadership Expectations This leader is expected to embody Micron’s core values and set the tone for the team: People Care for each other — build an inclusive, high-trust team; develop talent, grow capability, and plan succession across regions.
• Innovation Shape the future — champion agent-embedded ways of working; experiment, learn fast, and scale what works.
• Tenacity Nothing shakes our resolve — own data quality and value outcomes end-to-end through complex, cross-system challenges.
• Collaboration Aligned to win — break silos across DTAi, IT, Security, and the business; win as one team across time zones.
• Customer Focus Partner and win together — treat procurement stakeholders and end-users as customers; deliver trusted data that enables their decisions.
• Speed Act with purpose and set the pace — make timely, well-reasoned decisions and move prioritized data and AI work from pilot to scale without losing rigor. ▍ Leadership Competencies Talent & coaching: Develop, coach, and grow a multi-region team; build bench strength and succession within the function.
• Cross-cultural leadership: Lead effectively across U.S. and Asia cultures and time zones, creating an inclusive, globally minded team.
• Influence & partnership: Align IT, Security, and business stakeholders around common data standards without direct authority.
• Executive communication: Translate complex data topics into crisp, decision-ready narratives for senior leaders.
• Change leadership: Drive adoption of new standards and agent-embedded ways of working through enablement and change management.
• Outcome ownership: Set direction, prioritize ruthlessly, and hold the function accountable for measurable value. ▍ Minimum Requirements Education: Bachelor’s or Master’s degree in Information Systems, Data Science, Computer Science, Data/Information Management, Business Analytics, or a related quantitative or supply-chain field.
• Experience — depth: 10+ years in enterprise data management, analytics, or governance, including 5+ years leading data governance, master data management (MDM), or data quality programs and 3+ years leading teams.
• Experience — scale: At least 5 years in a large, multi-region enterprise (5,000+ employees) running on SAP (ECC and/or S/4HANA).
• Experience — domain: 3+ years working with procurement, sourcing, or supply-chain data, spanning several of Vendor/Business Partner Master, Material Master, Spend, Category Taxonomy, and Contracts.
• Governance model delivered: Designed and operationalized an enterprise data governance operating model (roles, decision rights, policies, data quality KPIs, stewardship) with measurable, sustained adoption.
• MDM / data catalog: Experience delivering programs on an MDM or data catalog platform (Informatica, Collibra, or Ataccama).
• SAP & Ariba: Hands-on familiarity with procurement data in SAP S/4HANA (or ECC) and SAP Ariba.
• Data & analytics foundations: Working knowledge of SQL, Snowflake, and Power BI or Tableau, plus data lineage, cross-system mapping, data dictionaries, and business glossaries.
• AI / agentic data: Experience defining data requirements for production AI/ML, automation, or agentic workflows — including data readiness, quality thresholds, and validation or feedback rules.
• Cross-functional leadership: Proven ability to influence IT, Security, and business stakeholders without direct authority on enterprise-scale, multi-region initiatives.
• Ways of working: Able to collaborate across US and Asia time zones, including regular overlap with US-based team members an