RES
Data and AI Governance Technical Lead
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Data and AI Governance Technical Lead
Do you want to Make Power for Good?
RES is the world's largest independent renewable energy company. Our mission is simple: a future where everyone has access to affordable, zero-carbon energy. The problems we're solving are among the most important of our generation — and the people working on them are extraordinary.
As AI adoption accelerates across the business, the integrity and trustworthiness of RES's data has never mattered more. This is a rare opportunity to own that — technically, practically, and at global scale.
The Role
As Data and AI Governance Technical Lead, you'll own the technical governance framework for enterprise data and analytics across Azure, Fabric, and Purview. You'll ensure data is classified, trusted, controlled, auditable, and safe for consumption by reporting, analytics, and AI tools in our global, centralised Azure Fabric data platform — and that governance is embedded into how the platform is built and operated.
This is a hands-on technical role. You'll implement controls, own Purview, define AI use case governance, and work closely with engineering, architecture, cyber, legal, and business teams to make governance real. You'll be the person who turns AI governance principles into practical, implementable technical controls.
You will also lead the delivery of a data governance framework for the globe, including data ownership, stewardship and support literacy and culture work, including chairing regular forums with senior executives.
What You'll Do
- Own and continuously mature the data governance framework across Fabric, Purview, and the AI-enabled IT Azure analytics platform.
- Support IT to author and maintain policies and standards for data quality, metadata, lineage, retention, privacy, and ethical data and AI usage.
- Support master and reference data alignment — developing definitions, KPIs, and semantic standards across global domains.
- Implement international data standardisation frameworks to ensure consistent definitions, taxonomies, and formats across regions.
- Implement and own Purview catalogue, classification, lineage, glossary, data ownership, and certified dataset processes end-to-end.
- Ensure all enterprise data assets are classified, owned, documented, and auditable.
- Embed governance metadata and lineage into data platform delivery as a standard engineering practice.
- Define and operate governance controls for AI-enabled data consumption through the central Azure data platform within IT.
- Define and enforce rules for what data and AI tools can and cannot access through the IT Azure data platform; ensure AI tools consume only approved, certified, and traceable data.
- Own audit evidence for AI-enabled data products in the Azure platform — maintaining complete, defensible records of data lineage, classification, approval, and access history.
- Support IT in enabling responsible AI practices including human oversight, explainability, traceability, bias assessment, and ethical use.
- Implement data quality management across the Azure platform — defining critical data elements, rule sets, monitoring, issue management, and remediation workflows.
- Establish data quality stewardship and data owner accountability across business domains.
- Automate data quality checks and embed them into CI/CD pipelines and data platform delivery processes.
- Partner with cyber and IT on data classification, access control, segregation of duties, and audit readiness.
- Work with legal, privacy, P&C, and business data owners to help ensure data use of enterprise data is safe, compliant, and auditable.
- Translate governance requirements into practical technical specifications for IT data engineers and data architects — and hold delivery teams accountable.
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What You'll Bring
- Microsoft Purview — deep hands-on expertise across metadata management, classification, glossary, lineage, and certified dataset governance in an Azure environment.
- AI governance — strong understanding of responsible AI, AI risk assessment, and AI control frameworks; ability to classify AI use cases by risk and define pre-go-live controls.
- Data governance strategy, frameworks, ownerships and stewardship - design, delivery, implementation and ongoing management.
- Technical control design — able to translate governance principles into implementable controls: prompt governance, output governance, data access restrictions, and audit evidence.
- Data quality — experience designing and operating data quality frameworks including profiling, rule design, monitoring, and root cause analysis.
- Privacy & compliance — working knowledge of GDPR, PII controls, and sensitive data handling with practical Azure implementation experience.
- Governance automation — experience embedding governance into CI/CD pipelines, data contracts, and automated platform checks.
- Stakeholder influence — comfortable leading executive forums and delivering regular executive presentations. Able to challenge unsafe practices and translating between technical teams, cyber, legal, privacy, and business.
- AI regulatory landscape — familiarity with NIST AI RMF, ISO 42001, EU AI Act, or equivalent frameworks.
Your Background
Essential
- Degree in data governance, data science, computer science, or a related field.
- Significant experience leading technical data governance in Microsoft Azure, with a proven track record of improving data quality, stewardship, and auditability using modern tooling.
- Extensive hands-on Microsoft Purview experience across an Azure data platform, with evidenced improvements to data quality and standardisation at global scale.
- Experience designing and implementing AI governance controls — including AI use case risk assessment, data access controls for AI tools, and audit evidence management.
- Experience governing sensitive enterprise data including personal data, employee data, and business-critical reporting data.
- Practical experience embedding governance into data platform delivery — CI/CD, automated checks, data contracts.
- Familiarity with AI governance frameworks such as NIST AI RMF, ISO 42001, or EU AI Act.
- Python or SQL used in a data quality or governance automation context.
- Relevant certifications: DAMA/CDMP, DCAM, CIPP, AIGP, Microsoft Azure, or equivalent AI or data governance credentials.
- Delivery of data governance frameworks, strategy, ownership and stewardship and driving change.
- Experience with automation tooling such as Power Platform, Power Automate, or equivalent applied to governance workflows.
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Why RES?
- A genuinely global data platform with real complexity and ambition behind it.
- A modern, cloud-first stack — Azure, Fabric, Synapse, and active investment in AI tooling.
- Own something that matters — as AI becomes central to how RES operates, data governance is a business-critical capability.
- A collaborative data function where governance is built in from the start.
- Join a brand new, agile, global data and analytics team at the heart of AI, innovation, Next Gen technology and driving innovation for competitive advantage for RES.
- You will have a diverse portfolio and be able to lead on many types of work, honing and developing strong skills in Artificial Intelligence to shape your future career at the forefront of the latest technologies.
- A collaborative, cross-functional data function with architecture, AI, science, analytics, and engineering working closely together.
- Competitive salary, benefits, and commitment to your professional development.
At RES, we celebrate differences as we know it makes our company a great place to work. Encouraging applicants with different backgrounds, ideas and points of view, we create teams who work together to solve complex problems and design practical solutions for our clients. Our multiple perspectives come from many sources including the diverse ethnicity, culture, gender, nationality, age, sex, sexual orientation, gender identity and expression, disability, marital status, parental status, education, social background and life experience of our people.
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