EAIG:Head – AI Data Engineering & Governance

• Define enterprise AI data architecture
• Own data governance, lineage, quality, and access controls
• Sponsor AI data platforms
• Manage senior architects and engineering leaders
• Interface with Risk, Compliance, IT Security

Work Areas & Outcomes -

AI data platforms are productiongrade, compliant, reusable, and trusted governance is embedded by design without
slowing innovation.

• 18-22 years senior leadership credibility in large regulated enterprises.

For successful execution of the job, the candidate should possess:

• Enterprise data architecture, governance frameworks, cloud data platforms, regulatory awareness, leadership maturity.