Data and AI Governance Technical Lead

Description

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.

As Data and AI Governance Technical Lead, you'll own the technical governance framework for enterprise data and AI across Azure, Fabric, and Purview. You'll ensure data is classified, trusted, controlled, auditable, and safe for consumption by reporting, analytics, and AI tools — 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.

At a time when the EU AI Act is reaching full enforcement and AI risk is a board‑level concern, this role sits at the centre of how RES manages that responsibly.

• Own and continuously mature the data and AI governance framework across Fabric, Purview, and the AI-enabled analytics platform.
• Author and maintain policies and standards for data quality, metadata, lineage, retention, privacy, and ethical data and AI usage.
• Drive master and reference data alignment — harmonising 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 — including the AI use case register covering risk rating, approval status, required controls, and review dates.
• Establish the technical control checklist required before any AI use case goes live: data source classification, ownership, access model, metric definition, lineage, prompt handling, output handling, and personal and sensitive data controls.
• Define and enforce rules for what data AI tools can and cannot access; ensure AI tools consume only approved, certified, and traceable data.
• Own audit evidence for AI-enabled data products — maintaining complete, defensible records of data lineage, classification, approval, and access history.
• Support responsible AI practices including human oversight, explainability, traceability, bias assessment, and ethical use; align to frameworks such as NIST AI RMF, ISO 42001, or the EU AI Act as applicable.

• Implement data quality management across the 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 Info Sec on data classification, access control, segregation of duties, and audit readiness.
• Work with legal, privacy, P&C, and business data owners to ensure AI use of enterprise data is safe, compliant, and auditable.
• Translate governance requirements into practical technical specifications for engineers and architects — and hold delivery teams accountable.
• Challenge unsafe AI use cases; communicate risk to both technical and non-technical stakeholders.

• Microsoft Purview — deep…