Enterprise Data Governance Architect

We are seeking anEnterprise Data Governance Architect to shape a scalable governance, cataloging, and security framework across a unified digital data ecosystem. You will partner with cross-functional teams to define stewardship, metadata, lineage, and quality standards that enable reliable analytics and compliant data sharing.

Responsibilities

• Define enterprise data governance frameworks, policies, and operating models for multi-country environments
• Architect metadata management, data cataloging, and automated data lineage capabilities
• Establish data quality metrics, monitoring rules, and stewardship workflows for trusted insights
• Align privacy compliance controls with security and legal stakeholders, including RBAC and cross-border data sharing
• Lead discovery workshops to assess data maturity, identify gaps, and define target-state roadmaps
• Coordinate with data engineering, analytics, architecture, and security teams to implement governance by design
• Advise stakeholders on scalable governance practices that enable secure, compliant analytics adoption

Requirements

• 5+ years of experience in enterprise data governance and operating model design
• Strong leadership skills to drive consensus and influence executive stakeholders
• Proven project delivery experience with multi-geo, cross-functional data programs
• Deep technical expertise in DAMA-DMBOK-aligned governance frameworks, metadata management, and data stewardship
• Hands-on cloud platform knowledge with Amazon Web Services and modern data stack architectures
• Strong consulting skills in workshop facilitation, stakeholder management, and change leadership
• Upper-Intermediate English proficiency (B2, Upper-Intermediate)

Nice to have

• AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect
• Experience with Databricks Unity Catalog and lineage/catalog tooling
• Knowledge of GDPR and regional privacy regulations in multi-country operations
• Experience with API-driven integration patterns in cloud data platforms