Director of Data Governance, Supply Chain Services

Company Overview
KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays.

The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices. Life here is exciting and our teams thrive on tackling really hard problems.

There is never a dull moment with us.

Job Description/Preferred Qualifications

Note to applicants: 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.

Role Summary

We are seeking a leader who's lived inside a regulated equipment business - and knows how to structure the Design Basis Information (DBI) required to support key regulated data elements, from the applicable regulatory requirements down to the standard supply chain operating practices around the globe. Design Basis Information is inclusive of the governing codes and regulations, the foundational business and compliance decisions, data element attributes and the associated design specifications.

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. Foundationally the framework design must enable enterprise standardization, facilitate cross-functional alignment, provide governance & controls, support a repeatable DBI methodology and be adoption-ready. This leader will work closely with the supply chain operations and compliance teams to enable trusted, interoperable data that supports compliance, operational excellence, analytics, AI, and digital transformation.

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.

Operating Model & Organizational Enablement

• 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.

Cross-Domain Data Alignment

• Enable harmonization and interoperability across key enterprise domains (e.g., customer, supplier, product, asset, manufacturing, service, finance) while respecting strong functional ownership.

• Define master data and reference DBI concepts, ownership, and synchronization approaches in the absence of a formal MDM tool.

Data Quality, Metadata & Standards

• 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…