Principal AI Data Strategist, Global Procurement

Micron Technology; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Micron Technology is seeking a Senior AI Data Strategist to transform Global Procurement’s data landscape for agentic AI deployment. You will tackle cross-system data challenges and design governance, quality, and lineage frameworks.

This hands-on role demands strong collaboration with IT, security, and business teams to enable scalable Source-to-Pay workflows. The position requires a Master’s in a quantitative field and 10+ years in enterprise data governance, with deep procurement data

Qualifications

• Master’s degree in Information Systems, Data Science, CS, or related field.
• 10+ years in enterprise data management with governance or data quality leadership.
• Hands-on experience with procurement, sourcing, or supply-chain data.
• Experience defining data requirements for production AI/ML or agentic workflows.

Responsibilities

• Lead reimagination of the procurement data landscape for agentic AI.
• Define data governance, quality monitoring, lineage, and lifecycle management.
• Build data lineage, mapping, and technical foundations for cross-system traceability.
• Coach stakeholders on working with data in an agent-embedded model.

Skills

Data governance

MDM

SQL

Procurement data

AI/ML readiness

Cross-system data

Education

Master's degree in Information Systems

Tools

Informatica

Collibra

Ataccama

Power BI

Tableau

SAP Ariba

Job description

Senior AI Data Strategist – Global Procurement

As a Senior AI Data Strategist within Global Procurement, you will lead the reimagination of the procurement data landscape so that agentic AI can execute Source-to-Pay work reliably, safely, and at scale. This is a hands‑on strategy and design role for a solid problem solver who thrives on untangling complex, cross‑system data challenges.

Key Responsibilities

• Move the procurement data function from reactive clean‑up to an agent‑embedded, self‑improving operating model.

Data Strategy and Reimagined Operating Model

• Reimagine the Data Governance and Excellence operating model with agents embedded, redefining policies, data quality monitoring, lineage, stewardship, and lifecycle management.
• Define the target working model, the agentic patterns that apply to data governance (data quality agent, lineage agent, maintenance agent, steward copilot), and a getting‑started roadmap sequenced against ERP and transformation milestones.

Data Readiness for Agentic Workflows

• Partner with agent build leads to define data elements, quality thresholds, and validation rules each agent needs, and map every business requirement to a data source, owner, and readiness action.
• Close gaps in master data element coverage so that lineage, definitions, and ownership are complete and agent‑consumable; stand up a searchable data dictionary and glossary both humans and agents can query.
• Design the feedback loop between agent, source system, and steward so that data validation, correction, and prevention happen without manual human touch wherever feasible.

Data Lineage, Mapping, and Technical Foundations

• Build working‑level technical foundations: data lineage, relationships, schema, and cross‑system mapping for traceability before change lands.
• Establish documentation, versioning, change history, and downstream impact analysis for agents to consume and update as first‑class users of the data catalog.
• Define control points at entry and prioritize critical data elements that drive downstream procurement value.

Governance, Policy, and Enterprise Partnership

• Partner with IT, Data Excellence, Security, and Compliance to align data strategy with enterprise controls, sensitivity labels, data loss prevention, and approved connectors.
• Contribute to lightweight, machine‑readable policies and standards that agents enforce automatically, shifting governance from static documents to executable rules.
• Establish data quality KPIs, SLAs, and monitoring so quality is measurable and managed, not assumed.

Innovation, Experimentation, and Reusable Assets

• Run rapid experiments on agentic data patterns (data quality agent, lineage agent, maintenance agent, steward copilot), validate impact, and turn the best into reusable building blocks for broader reuse.
• Pilot AI‑based data validation and cleansing tools and assess fit against Micron's data landscape.

Cross‑Functional Leadership and Enablement

• Coach data stewards, custodians, category managers, and business owners on working with data in an agent‑embedded model.
• Coordinate with automation, agent build, and AI strategy teams; represent the data agenda in program reviews and executive readouts.

Minimum Requirements

• Master’s degree in Information Systems, Data Science, Computer Science, Data/Information Management, or a related quantitative field.
• 10+ years in enterprise data management, including 6+ years leading data governance, MDM, or data quality programs in a large, multi‑region SAP environment.
• Hands‑on experience with procurement, sourcing, or supply‑chain data.
• Experience with data lineage, cross‑system mapping, data dictionaries, business glossaries, and working SQL proficiency.
• Direct experience defining data requirements for production AI/ML or agentic workflows, including data readiness, quality thresholds, and validation or feedback rules.
• Proven ability to influence IT, Security, and business stakeholders without direct authority.

Preferred Requirements

• Experience reimagining a data governance operating model with AI or agents embedded.
• Experience in Source‑to‑Pay, Procure‑to‑Pay, or Supply Chain data domains (Vendor Master, Material Master, Spend, Category Taxonomy, Contracts).
• Designed and operationalized an enterprise data governance operating model with measurable adoption.
• Hands‑on implementation of MDM or data catalog platform (Informatica, Collibra, or Ataccama).
• Familiarity with ERP migration data readiness, machine‑readable policies, and DLIP and sensitivity‑label impacts on AI connector access.
• Additional certifications in data management, AI, analytics, or procurement transformation.
• Hands‑on experience with SAP Ariba procurement data (sourcing, contracts, or spend).
• Hands‑on experience with cloud data platforms (Snowflake) and enterprise BI tools (Power BI or Tableau).
• Comfort collaborating across US and Asia time zones, with regular overlap with US‑based stakeholders.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

To request assistance with the application process and/or for reasonable accommodations, please contact [e-mail].