Key Responsibilities :

Enterprise Data Governance Strategy :

- Define and execute the enterprise data governance roadmap.

- Establish governance processes, operating models, stewardship responsibilities, and accountability frameworks.

- Develop standards for data quality, metadata management, lineage, classification, and access governance.

- Drive adoption of governance practices across business and technology teams.

Metadata & Knowledge Management :

- Lead implementation and optimization of Atlan, Alation, Purview, or similar governance platforms.

- Build and maintain enterprise business glossaries, taxonomies, and knowledge frameworks.

- Establish metadata standards that improve discoverability and trust in enterprise data assets.

- Create governance processes for capturing business context and institutional knowledge.

Semantic Layer & Data Products :

- Define enterprise semantic layer strategy across analytics and AI platforms.

- Partner with domain teams to create governed business metrics and standardized definitions.

- Establish lifecycle management for data products and certified data assets.

- Enable consistent business logic across reporting, analytics, AI solutions, and self-service platforms.

AI & Agent Readiness :

- Establish governance frameworks for AI-ready data assets.

- Create structures that enable AI systems and autonomous agents to understand business context, metrics, definitions, and relationships.

- Define standards for contextual metadata, business rules, semantic relationships, and knowledge representation.

- Partner with AI and Data Science teams to ensure trusted, governed data is available for AI applications.

- Develop governance controls for AI-generated insights and agent-based decision support systems.

Data Quality & Trust :

- Establish enterprise-wide data quality standards, monitoring, and remediation processes.

- Define critical data elements and associated quality metrics.

- Develop trust scores, certification processes, and governance workflows for enterprise data assets.

- Drive continuous improvement of data reliability and usability.

Lineage & Impact Analysis :

- Build end-to-end visibility of data lineage across enterprise platforms.

- Establish impact analysis processes for changes to critical data assets.

- Improve transparency into how data moves from source systems through analytics and AI applications.

- Support compliance, audit, and operational risk management requirements.

Stakeholder Leadership :

- Partner with business leaders to define ownership and stewardship for critical data domains.

- Facilitate governance councils and cross-functional data communities.

- Drive adoption and organizational change management initiatives.

- Influence senior leaders on the strategic value of governance, semantic layers, and AI-ready data foundations.

Required Qualifications :

- 8+ years of experience in Data Governance, Metadata Management, Data Architecture, Analytics, or related disciplines.

- Hands-on experience with Atlan, Alation, Microsoft Purview, Collibra, or comparable governance platforms.

- Strong understanding of metadata management, business glossaries, lineage, cataloging, and data quality frameworks.

- Experience building semantic models, business metrics frameworks, and governed data products.

- Understanding of modern cloud data platforms including Azure, Snowflake, Databricks, and Microsoft Fabric.

- Experience driving cross-functional governance programs in large enterprises.

- Strong communication and stakeholder management skills.