Contract - £650 / Day - Outside IR35 - 12 months

TL;DR

• Role: Data Governance & Master Data Lead — standing up an enterprise data governance function from scratch
• Where you'll work: Embedded on-site with a global renewable energy developer and operator
• Location: London — on-site, five days a week
• Type: Permanent, full-time
• Domain: Utilities, energy or another asset-heavy industry — essential, not a nice-to-have
• Platforms: SAP MDG, Informatica MDM, Collibra or Microsoft Purview; SAP S/4HANA environment
• Line Management: Lead a Master Data team of internal staff, outsourced specialists and consultants
• Visa Sponsorship: Not available — you must already have the right to work in the UK
• Flexibility: This one is genuinely full-time and on-site. If that does not work for you, we have other roles that will
• Diversity & Inclusion: We want a broad mix of people and perspectives

Who We Are

Hypercube is a data-and-AI specialist focused on the energy sector. We pair deep domain know-how with modern technology to help utilities, renewables and low-carbon innovators get value out of their data.

We put our best people directly alongside clients, embedded in their world, solving real operational problems. This role is one of those: a permanent Hypercube hire, deployed on-site with a global renewable energy developer and operator whose portfolio spans utility-scale solar, onshore and offshore wind, storage and green hydrogen across dozens of countries.

Role Purpose

The client's growth has outrun its data foundations. Asset data, financial data, supply chain data and corporate data live in different systems, carry different definitions, and answer to different people. Nobody owns the turbine hierarchy. The plant list in the ERP does not match the one in the EAM. Finance cannot close on numbers it trusts without someone reconciling by hand.

You are being hired to fix that permanently, as the custodian of enterprise data trust.

This is a build role, not a maintenance role. There is no framework to inherit and no committee to join. You define the operating model, win the mandate, appoint the owners and stewards, select the platform, and prove the value — while the business keeps commissioning assets around you.

It suits someone who has done this before at scale in an asset-heavy industry, who can hold a room of senior stakeholders without formal authority over a single one of them, and who is as comfortable chairing a Data Governance Committee as working out why the component hierarchy broke.

Key Responsibilities

• Governance Framework: Define and implement a Data Governance Framework aligned to DAMA-DMBOK, Gartner and leading utility practice. Build a federated operating model that scales globally while keeping accountability local
• Ownership Model: Establish Data Owners, Stewards and Custodians across business and IT — named people, real accountability, not a RACI nobody reads
• Committee & Mandate: Chair the enterprise Data Governance Committee. Drive alignment across functions and hold them to the numbers on coverage, completeness and accuracy
• Policy & Compliance: Develop and enforce policies and controls across data classification, privacy and lifecycle management. Cover ESG and energy regulatory reporting obligations, and align to ISO, NIST and sector standards
• Master Data: Own enterprise MDM strategy across asset master data (plants, turbines, components), customer and offtaker data, and supplier and vendor data. Establish the golden source across ERP, EAM and SCADA interfaces, starting with financial use cases
• Platform: Run MDM platform selection, then own implementation and adoption — SAP MDG, Informatica MDM or equivalent
• Data Quality: Define and track KPIs across accuracy, completeness, consistency and timeliness. Put automated monitoring and remediation in place. Lead root-cause analysis on the systemic issues
• Business Integration: Partner with Generation, O&M, Finance and Supply Chain to push accountability into the business. Translate between technical teams and leadership so governance gets adopted rather than published
• Team & Vendors: Lead the Master Data team, internal and outsourced. Manage external specialists and advisory partners — scope, KPIs, deliverables, cost
• Benchmarking: Benchmark against NextEra, RWE, DEWA and TAQA. Assess AI-enabled governance, metadata management and catalogue platforms, and get data ready for advanced analytics and AI