Data Governance Lead

RES

9h

About The Position

Do you want to work to make Power for Good? We're the world's largest independent renewable energy company. We're guided by a simple yet powerful vision: to create a future where everyone has access to affordable, zero carbon energy. We know that achieving our ambitions would be impossible without our people. Because we're tackling some of the world's toughest problems, we need the very best people to help us. They're our most important asset so that's why we continually invest in them. RES is a family with a diverse workforce, and we are dedicated to the personal professional growth of our people, no matter what stage of their career they're at. We can promise you rewarding work which makes a real impact, the chance to learn from inspiring colleagues from across a growing, global network and opportunities to grow personally and professionally. Our competitive package offers a wide range of benefits and rewards. Job Summary The Group Lead for Data Governance owns and matures the enterprise data governance framework across domains (e.g., Finance, HR and core operational data). Establishes clear data ownership, policies, standards, controls and assurance so that reporting, analytics and AI/ML use cases are trusted, compliant and auditable. They work with business data owners/stewards, IT security, architecture, engineering and analytics teams to embed governance into ways of working, tooling and project delivery. The data governance lead is responsible for ensuring the data and analytics data platform, analytics and reporting are secure and that data quality is continuously improved across core global data domains, particularly focusing on corporate services data.

Requirements

• Strong knowledge of data governance, data management and controls (DCAM/DAMA principles or equivalent).
• Hands-on understanding of metadata management, data catalogues, lineage, business glossaries and stewardship workflows.
• Data quality engineering concepts: profiling, rule design, monitoring, incident triage, root cause analysis.
• Privacy and regulatory awareness (e.g., GDPR) and practical implementation of PII controls and minimisation.
• Ability to translate between technical and business audiences; influence without authority at global scale.
• Experience embedding governance into delivery pipelines (CI/CD, data contracts, automated checks).
• Working knowledge of AI and machine learning and related controls.
• Strong facilitation, stakeholder management, and operating-model design skills.
• Bachelor’s degree in Data Analytics, Data Science, or a related field
• Significant experience leading data governance or data management programmes in complex, global organisations.
• Proven track record establishing global stewardship and data ownership and improving data quality outcomes.
• Extensive experience with modern Azure data platforms in a global context with multiple complex integrations and source systems (cloud data Lakehouse/warehouse patterns) and governance tooling (catalogue/lineage – specifically Microsoft Purview).
• Experience in implementing Microsoft Purview across an Azure Data Platform with evidence improvements to data quality, standardisation of corporate services data in a global context.
• In depth knowledge and practical implementation of compliance frameworks and global employment regulations.
• Knowledge of international data standardization frameworks for harmonizing data definitions, taxonomies, and formats across regions, specifically in relation to IFS (RES’s enterprise ERP system) and must have extensive experience in financial and human resources data governance in a global context.
• Experience in AI/ML use cases and governance requirements.

Nice To Haves

• Relevant qualifications/certifications beneficial (e.g., DAMA/CDMP, DCAM, privacy certification), or equivalent experience.

Responsibilities

• Define and run the global data governance operating model.
• Stand up and maintain domain data ownership and stewardship; coach and enable stewards and data product owners.
• Author and maintain policies/standards for data quality, metadata, lineage, retention, privacy, and ethical data/AI usage.
• Implement data quality management: critical data elements, rule sets, monitoring, issue management and remediation workflow.
• Drive master/reference data principles and alignment of definitions, KPIs and semantic standards across domains.
• Partner with Cyber/InfoSec on data classification, access control, segregation of duties, and audit readiness.
• Own governance tooling and processes (catalogue, glossary, lineage, approvals) and ensure adoption.
• Support AI/ML governance: model risk controls, data suitability checks, bias/ethical considerations, and monitoring.
• Produce governance reporting for executives (compliance, quality trends, maintain and control risks and issues, lead controls and remediation).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees