RES
Data and AI Governance Technical Lead
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Data and AI Governance Technical Lead
Data and AI Governance Technical Lead
Make Power for Good
RES is the world’s largest independent renewable energy company. Our mission is 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 data governance—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 AI across Azure, Fabric, and Purview. You’ll ensure data is:
- Classified and trusted
- Controlled and auditable
- Safe for consumption by reporting, analytics, and AI tools
- Embedded as a standard operating practice in the platform’s development and operations
This is a hands-on, technical role where you’ll architect configurations, own Microsoft Purview, define AI use case governance, and collaborate closely with engineering, architecture, cybersecurity, legal, and business teams to operationalise governance effectively. At a time when European AI compliance (EU AI Act) is critical, your role sits at the centre of responsible data and AI governance, directly shaping how RES articulates and mitigates risk to the board level.
What You’ll Do
Governance Framework & Standards
- Own, refine, and implement the cross-geography, cross-product governance framework for data and AI in Fabric, Purview, and the broader analytics platform.
- Define and maintain policies and standards covering:
- Data quality
- Metadata management
- Lineage tracking
- Retention and archiving
- Privacy and safeguarding against bias/ethics risks
- Drive master data alignment, harmonising definitions, KPIs, semantic standards, and global taxonomy for consistency across domains.
- Deploy international data standard frameworks (e.g., PCI, ISO, NIST) to ensure uniform definitions, taxonomies, and formats.
Microsoft Purview & Data Catalogue
- End-to-end ownership of Purview’s metadata, classification, lineage, glossary, and certified dataset processes.
- Ensure full visibility and accountability over enterprise data assets with structured classification, ownership records, and audit trails.
- Embed governance metadata and lineage into engineering development as a default process—ensuring traceability by design.
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AI Governance & Control
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Define and enforce AI-specific governance controls, including:
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Use-case risk assessment (classification by risk level, approval workflows, mandatory controls)
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Pre-delivery checklist for AI use cases:
- Data source classification & ownership
- Access model & sensitivity controls
- KPI and lineage requirements
- Prompt と output validation
- Protection for personal and sensitive data
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Governance of AI interaction:
- Data access rules (which datasets AI can consume)
- Assurance that AI tools only use certified and traceable data
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Maintain defensible audit evidence for AI-enabled data products—tracking lineage, classification, approvals, and access histories.
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Promote responsible AI practices:
- Human oversight, explainability, and bias mitigation
- Adherence to frameworks such as NIST AI RMF, ISO 42001, and EU AI Act
Data Quality
- Implement data quality management systems to:
- Define critical data elements and rules
- Monitor compliance and manage remediation
- Integrate checks into CI/CD pipelines
- Foster data stewardship by assigning clear ownership across business functions.
- Automate quality checks and embed governance directly into the data platform.
Cross-functional Partnership
- Collaborate with cybersecurity and InfoSec teams to:
- Classify data assets
- Enforce access controls and segregation of duties
- Ensure audit readiness
- Work with legal, privacy, contract (P&C), and domain owners to align governance with regulatory requirements and business priorities.
- Translate governance technical specifications into clear guidance for engineers and architects, holding teams accountable.
- Proactively identify unsafe AI use cases, communicating risks to both technical and non-technical stakeholders.
What You’ll Bring
Essential Expertise
- Deep hands-on expertise in Microsoft Purview across:
- Metadata management
- Classification & certification
- Lineage tracking & glossaries
- Certified data assets in Azure environments
- Strong understanding of responsible AI governance, including:
- AI risk assessment frameworks
- Pre-launch controls (prompt governance, output validation, ethical use)
- Technical control design: Ability to translate governance principles into concrete mechanisms for:
- AI-driven data governance
- Change controls, access restrictions
- Audit trails
- Proven data quality experience, including:
- Data profiling
- Rule design
- Fault resolution
- Root cause analysis
- Practical knowledge of GDPR, PII protection, and sensitive data handling with direct Azure implementations.
- Hands-on experience embedding governance into CI/CD and data delivery.
- Working knowledge of AI regulatory frameworks: NIST AI RMF, ISO 42001, EU AI Act.
- Bachelor's degree in data governance, data science, computer science, or a related field—or equivalent experience.
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Desirable Competencies
- Automation experience with:
- Microsoft Power Platform/Power Automate, or similar
- Python/SQL for quality or governance automation workflows
- Relevant certifications:
- DAMA/CDMP, DCAM, CIPP, AIGP, Microsoft Azure certifications
- Any AI or data governance-track credentials
Why RES?
We’re making the highest-impact use of technology to seize a cheshiring imagination outcome—expanding access to clean energy. Here’s what you’ll get:
- Impact at scale: Data governance isn’t a periphery function—it’s the cornerstone of trust in AI-driven decision-making at a global company.
- Cutting-edge tech stack: A dynamic Azure/Fabric/Purview environment with continuous investment in scale and modern architecture.
- Proactive culture: Governance isn’t bolted on—it’s architected into the DNA of our data platform.
- Rewarding opportunities:
- Competitive compensation aligned with experience
- Benefits-focused plan for career maturation (mentorship, certifications, learning stipends)
- Commitment to fostering equity and making technology work for everyone
At RES, we are diverse. We celebrate hands, perspectives, and skills that accumulate to push boundaries—regardless of ethnicity, bias, culture, gender, gender identity, disability, parental status, or other attributes. All are encouraged to apply.
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