AI Data Governance Implementation Lead
Who we are
The next step of your career starts here, where you can bring your own unique mix of skills and perspectives to a fast-growing team.
Metyis is a global and forward-thinking firm operating across a wide range of industries, developing and delivering AI & Data, Digital Commerce, Marketing & Design solutions and Advisory services. At Metyis, our long-term partnership model brings long-lasting impact and growth to our business partners and clients through extensive execution capabilities
With our team, you can experience a collaborative environment with highly skilled multidisciplinary experts, where everyone has room to build bigger and bolder ideas. Being part of Metyis means you can speak your mind and be creative with your knowledge. Imagine the things you can achieve with a team that encourages you to be the best version of yourself.
We are Metyis. Partners for Impact.
What we offer
A hands-on opportunity to help clients build and embed Data and AI Governance in practice, moving beyond frameworks into real business impact.
The opportunity to shape reusable governance building blocks, including templates, playbooks, ways of working and practical implementation approaches.
Regular interaction with senior business, Data, AI and IT stakeholders to drive governance adoption and responsible use of data and AI.
Collaboration with multidisciplinary teams across Data, Analytics, AI, Architecture, Privacy and Security.
Exposure to complex enterprise data environments and evolving AI technologies, governance practices and responsible AI principles.
What you will do
Help clients turn Data and AI Governance from concept into daily practice, starting with areas where business value, risk and stakeholder buy-in are highest.
Identify priority stakeholders, business pain points and governance gaps together with Business, Data, AI and IT teams.
Define clear governance ownership and accountability, including Data Owners, Data Stewards, Data Custodians and relevant governance forums, and support stakeholders in adopting these responsibilities.
Facilitate workshops to align business and technical stakeholders on ownership, definitions, decision-making and governance requirements.
Translate broad and ambiguous Data and AI Governance challenges into clear, actionable implementation approaches.
Support the implementation and embedding of governance into day-to-day ways of working, including data quality, ownership, metadata, lineage, access, privacy and appropriate AI usage.
Work with AI, Data, Architecture, Privacy and Security teams to ensure AI initiatives are built on reliable, secure, well-governed and trusted data foundations.
Support governance considerations for AI solutions, including data quality, traceability, privacy, security, accountability and responsible AI practices.
Participate in governance forums and help ensure key Data and AI decisions, risks and responsibilities are clearly documented and understood.
Turn successful approaches into reusable templates, playbooks and accelerators that can be applied across projects and clients.
What you will bring
4–6 years of experience in Data Governance, Data Management, Data Quality, Analytics, Business Analysis or a related field, with exposure to AI/ML environments or AI governance being highly valuable.
Experience initiating a data or governance effort from scratch, including securing sponsorship and stakeholder buy-in rather than only operating within an established governance model.
Strong understanding of core Data Governance concepts, including data ownership, stewardship, data quality, metadata, lineage and governance processes.
Good understanding of how data quality, governance, privacy and security affect AI solutions and their trustworthiness.
Awareness of AI/ML concepts and lifecycle considerations, with the ability to engage effectively with AI, Data and technical teams. Hands-on AI development is not required.
Ability to take a broad or ambiguous mandate and structure it into a clear starting point and practical implementation roadmap.
Strong stakeholder-management and communication skills, with the ability to translate Data and AI Governance concepts into business value for both technical and non-technical audiences.
Comfortable engaging senior business stakeholders directly and building relationships across Business, Data, AI and IT teams.
Proactive, pragmatic and comfortable working with ambiguity in complex enterprise environments.
Nice to have
Familiarity with governance frameworks such as DAMA-DMBOK/CDMP or tools such as Collibra, Informatica, Alation or Microsoft Purview.
Awareness of Responsible AI / AI Governance principles, including transparency, accountability, privacy, security and human oversight.
Exposure to cloud/data/AI platforms such as Azure, Databricks or similar enterprise environments.
Experience in consulting, international or multi-entity organisations.
Basic SQL, BI or data-platform knowledge and awareness of GDPR or other data-protection principles.
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