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Director of Data Governance, Supply Chain Services
Job in
Milpitas, Santa Clara County, California, 95035, USA
Listed on 2026-07-04
Listing for:
KLA-Belgium
Full Time
position Listed on 2026-07-04
Job specializations:
-
IT/Tech
Change Management, Data Security
Job Description & How to Apply Below
Role Summary
This is not an IT Data Governance role but rather a position focused on creating data governance for design basis information to facilitate export of parts and materials with regulatory compliance requirements. The Director of Data Governance will design and implement a scalable enterprise framework to derive and govern the design basis for the regulated data elements supporting KLA’s supply chain and trade operations.
Key Responsibilities Enterprise Data Governance Strategy & Framework- Define and implement an enterprise DBI governance vision aligned to business strategy, regulatory needs, and digital/AI ambitions.
- Design a scalable governance framework covering data domains, ownership, stewardship, policies, standards, controls, and decision rights.
- Establish a pragmatic governance maturity roadmap, balancing speed-to-value with long-term sustainability.
- Define and stand‑up the DBI governance operating model, including roles (DBI owners, data stewards, custodians), forums, and escalation paths.
- Lead the formation of a cross‑functional DBI Governance Council and domain‑level working groups.
- Drive adoption through clear incentives, lightweight processes, and embedded governance within business workflows.
- Enable harmonization and interoperability across key enterprise domains (e.g., customer, supplier, product, asset, manufacturing, service, finance) while respecting functional ownership.
- Define master data and reference DBI concepts, ownership, and synchronization approaches in the absence of a formal MDM tool.
- Establish DBI quality management practices, including critical data elements, quality rules, monitoring, and remediation workflows.
- Define enterprise DBI standards, naming conventions, and semantic alignment to support analytics and AI use cases.
- Lead implementation of metadata management practices (business, technical, and operational metadata), including data lineage and glossary development.
- Develop an assurance process for the DBI associated with each critical data element to ensure continued compliance with regulatory standards.
- Comply with KLA’s data‑related policies and standards (e.g., data access, classification, retention, privacy, and usage).
- Partner with Legal, Security, Privacy, and Compliance teams to ensure governance supports regulatory and contractual requirements.
- Support audit readiness and risk mitigation related to data.
- Define governance requirements for tools supporting DBI metadata, quality, and lineage.
- Evaluate and recommend governance and data‑management tooling as needed, without assuming immediate MDM deployment.
- Ensure governance is embedded into analytics platforms, ERP, PLM, MES, CRM, and digital platforms.
- Drive cultural adoption of data as an enterprise asset through communication, training, and executive engagement.
- Translate governance concepts into business‑relevant outcomes for manufacturing, supply chain, trade, service, engineering, and commercial teams.
- Act as a trusted advisor to senior leaders on supply chain DBI and data‑related decisions and tradeoffs.
- 12+ years of experience in data management, data governance, analytics, or related disciplines, with at least 5 years in a senior governance leadership role.
- Direct experience operating within a mature, regulated equipment business environment.
- Demonstrated success building or transforming governance capabilities in a complex, federated organization.
- Strong understanding of data governance frameworks and practical, real‑world regulated market applications.
- Proven ability to influence senior stakeholders and lead through ambiguity and change.
- Experience in advanced equipment manufacturing or industrial technology environments and/or regulated operating environments (aviation, power generation, medical devices, etc.).
- Familiarity with ERP, PLM, MES, CRM, and analytics platforms common in manufacturing ecosystems.
- Experience supporting analytics, AI/ML, or digital…
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