AI Data Governance Implementation Lead

About the role

Metyis is seeking an AI Data Governance Implementation Lead to help clients embed data and AI governance into daily practice, turning concepts into tangible business impact.

Key responsibilities

• Identify priority stakeholders, business pain points and governance gaps, and define clear ownership and accountability for data and AI.
• Facilitate workshops to align business and technical teams on governance requirements, and translate broad challenges into actionable implementation approaches.
• Support the embedding of governance into day‑to‑day processes, covering data quality, metadata, lineage, access, privacy and responsible AI usage.
• Collaborate with multidisciplinary teams (Data, AI, Architecture, Privacy, Security) to ensure AI initiatives are built on trusted, well‑governed data foundations.
• Develop reusable templates, playbooks and accelerators to apply successful governance approaches across projects and clients.

Required profile

• 4–6 years of experience in Data Governance, Data Management, Data Quality, Analytics or related fields, with exposure to AI/ML environments.
• Proven ability to launch governance initiatives from scratch, securing sponsorship and stakeholder buy‑in.
• Strong understanding of data ownership, stewardship, metadata, lineage and governance processes.
• Excellent stakeholder‑management and communication skills, able to engage senior business leaders.
• Proactive, pragmatic and comfortable working with ambiguity in complex enterprise settings.

Required skills

• SQL
• Business Intelligence (BI) tools
• Collibra, Informatica, Alation or Microsoft Purview
• Azure, Databricks or similar cloud/data/AI platforms
• Knowledge of GDPR or other data‑protection principles

What we offer

• Hands‑on opportunity to shape data and AI governance practices for leading organisations.
• Interaction with senior business, data, AI and IT stakeholders.
• Collaboration with multidisciplinary teams across Data, Analytics, AI, Architecture, Privacy and Security.
• Exposure to complex enterprise data environments and evolving AI technologies.