R&D Data Governance Lead

Qcells is seeking an R&D Data Governance Lead to establish and manage data governance practices across global R&D environments. The role addresses fragmented data practices by defining clear ownership, standards, quality expectations, and access principles - enabling trusted analytics and AI capabilities across R&D.

You will work with global R&D teams, Digital Transformation, IT, security, legal, and regional site teams to ensure R&D data is trusted, protected, and fit for use., * Lead development and implementation of R&D data governance frameworks, standards, and operating practices.

• Define data ownership, stewardship, and decision rights across priority R&D data domains (equipment, process, material, experiment, reliability, and product data).
• Establish data quality expectations - completeness, accuracy, consistency, traceability - and work with technical teams to embed these into platform capabilities.
• Define metadata standards, naming conventions, lineage expectations, and data definitions for critical R&D datasets.
• Develop processes for managing access requests, usage rules, data quality issues, and governance escalations.
• Define governance expectations for AI-enabled use cases, including source data documentation, access controls, and appropriate use.
• Monitor governance maturity and provide visibility into risks, gaps, and improvement priorities.
• Support change management to help R&D teams understand and adopt data standards and governance expectations.
• Serve as the internal governance owner for R&D data trust and AI-readiness beyond individual projects or vendor engagements.

• Bachelor’s degree in Information Systems, Data Management, Business, Engineering, Computer Science, or a related field.
• 6+ years of experience in data governance, data management, data quality, or enterprise analytics governance, including demonstrated ownership of a governance or data management initiative from design through adoption.
• Strong understanding of data ownership, metadata, data quality, lineage, and access management.
• Experience defining governance processes, data standards, and accountability models across technical and business stakeholders.
• Strong communication, facilitation, and stakeholder alignment skills., * Experience in R&D, manufacturing, solar, semiconductor, materials science, or industrial automation environments.
• Familiarity with data catalog, metadata management, or data quality tooling (e.g., Purview, Alation, Collibra, or similar).
• Experience working alongside data platform, IT, security, or legal teams in a matrix organization.
• Exposure to AI/ML, analytics governance, or digital transformation programs.

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