Data Governance Architect
Listed on 2026-08-03
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IT/Tech
Information & Knowledge Management, Information Security & Data Protection, Data Engineering, Data Warehousing
Innovation starts from the heart. At Edwards Lifesciences,we’rededicated to developing ground-breaking technologies with a genuine impact on patients’ lives. At the core of this commitment is our investment incutting-edgeinformation technology. This supports our innovation and collaboration on a global scale, enabling our diverse teams to optimize both efficiency and success. As part of ourITteam, your expertise and commitment will help facilitate our patient-focused mission by developing and enhancing technological solutions.
The Data Governance Architect partners with business and technical stakeholders to design, develop, and implement data governance architecture, standards, and integration patterns that support enterprise data management objectives. This role translates business requirements into scalable architectural solutions, establishes governance standards and best practices, and provides technical leadership for data governance initiatives across the enterprise.
How you’ll make an impact:Governance Architecture & Design
- Translate business and data governance requirements into repeatable architecture patterns, standards, and design strategies for data management initiatives.
- Define and maintain the data governance architecture, including data quality, metadata, lineage, access management, and stewardship capabilities.
- Collaborate with project teams to ensure governance solutions align with enterprise architecture standards and strategic technology direction.
- Develop architectural recommendations that support scalability, maintainability, and interoperability across the data ecosystem.
- Identify opportunities to integrate data governance capabilities across platforms, applications, and business processes.
- Define interfaces, data flows, shared data assets, and metadata requirements that enable consistent governance practices.
- Partner with data engineering, platform, and business teams to support implementation of governance controls and data quality processes.
- Monitor the effectiveness of governance solutions and recommend enhancements to improve business outcomes.
- Develop, maintain, and promote data governance standards, architectural methodologies, and implementation best practices.
- Establish reusable patterns that support consistent adoption of governance controls across projects and platforms.
- Contribute to enterprise architecture and data management frameworks.
- Provide oversight to ensure compliance with approved architecture standards, governance policies, and data management practices.
- Participate in architecture reviews and design discussions to ensure alignment with established principles and standards.
- Support governance initiatives related to data quality, metadata management, lineage, and access management.
- Evaluate emerging technologies, tools, and methodologies that may enhance data governance and data management capabilities.
- Provide recommendations regarding adoption and integration of new solutions within the enterprise architecture landscape.
- Support the development and maintenance of metadata, governance artifacts, and architectural documentation repositories.
- Promote standards for documentation, traceability, and architecture lifecycle management.
- Provide expert guidance to project teams on data governance architecture and implementation approaches.
- Coach and mentor team members on governance standards, architecture principles, and best practices.
- Promote knowledge sharing and adoption of governance capabilities across the organization.
- Communicate architectural concepts effectively to both technical and business stakeholders.
- Bachelor's Degree in Computer Science, Information Systems, Natural Sciences and Mathematics or a related discipline and ten years of IT related experience
- Experience in data architecture, data management, data governance, or related technology disciplines.
- Familiarity with data catalog, lineage, data quality, and…
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