Head of Data Platform

When you join EDF Trading, you’ll become part of a diverse international team of experts who challenge conventional ideas, test new approaches, and think outside the box.

Energy markets evolve rapidly, so our team needs to remain agile, flexible, and ready to spot opportunities across all the markets we trade in power, gas, LNG, LPG, oil, and environmental products.

EDF Group and our customers all over the world trust that their assets are managed by us in the most effective and efficient manner and are protected through expert risk management. Trading for over 20 years, it’s experience that makes us leaders in the field. Energy is what we do.

Become part of the team and you will be offered a great range of benefits, which include (location dependent) hybrid working, a personal pension plan, private medical and dental insurance, bi-annual health assessments, corporate gym memberships, an electric car lease programme, childcare vouchers, a cycle-to-work scheme, season ticket loans, volunteering opportunities, and much more.

Gender balance and inclusion are very high on the agenda at EDF Trading, so you will become part of an ever-diversifying family of around 750 colleagues based in London, Paris, Singapore, and Houston. Regular social and networking events, both physical and virtual, will ensure that you always feel connected to your colleagues and the business.

Who are we? We are EDF Trading, part of the EDF Group - a world leader in low-carbon, sustainable electricity generation.

Join us, make a difference, and help shape the future of energy.

Job Description:

Department

Information Technology – Data Platform

Position Purpose

Own EDF Trading's enterprise data strategy and the capabilities required to provide trusted, governed and readily usable data. The role leads data product management, market data systems, core data engineering, plus data governance and quality. You will be accountable for turning data into a managed enterprise asset while enabling analytics, advanced modelling and AI at scale.

Main Responsibilities

• Define and execute the enterprise data strategy, target architecture, operating model and multi-year roadmap in alignment with business and technology strategy.
• Lead data product management, market data systems, core data engineering, and data governance and quality as an integrated enterprise capability.
• Establish accountable ownership for critical data domains, datasets and data products, with clear quality requirements, service expectations and lifecycle plans.
• Prioritise investment and delivery across ingestion, streaming, APIs, warehousing, reporting and advanced analytics capabilities.
• Ensure metadata, lineage, data quality controls, access controls, retention, privacy and control evidence are embedded into platforms and delivery practices.
• Build strong partnerships across the trading, operations, risk, finance and corporate functions to convert business needs into reusable data products rather than one-off pipelines.
• Own the market data capability, including distribution, entitlements, vendor strategy, usage transparency, cost management and resilience.
• Provide governed enablement for data science and AI, including trusted training data, reproducibility, model lifecycle dependencies and responsible-use controls.
• Set measures for data reliability, quality, adoption, delivery flow, platform performance, cost and value realisation.
• Develop senior leaders and specialist teams, balancing central standards with federated domain accountability and avoiding duplicated data engineering.

Experience Required

• Substantial leadership experience across enterprise data, data engineering, data governance, analytics or data product management in a complex organisation.
• Demonstrable delivery of enterprise-scale data platforms and operating models, ideally in energy trading, commodities or financial services.
• Experience managing critical market, trade, reference, risk, finance or regulatory data with demanding quality, timeliness and control requirements.
• Track record of building multidisciplinary teams and leading material change across technology and business functions.
• Experience of vendor and commercial management for data platforms, cloud services and market data providers.
• Strong executive-level communication, investment governance and benefits management experience.

Technical Requirements

• Deep understanding of modern data architecture, including event streaming, Kafka, APIs, batch ingestion, lakehouse patterns, data warehousing and real-time distribution.
• Strong knowledge of data engineering practices using SQL and relevant programming languages, storage design, performance optimisation, testing, deployment and observability.
• Practical expertise in metadata management, lineage, data quality, master and reference data, ownership models, access governance and control assurance
• Understanding of analytics, reporting, machine learning and AI lifecycles, including data preparation, feature provenance, monitoring and governance.
• Knowledge of cloud and hybrid architecture, cybersecurity, privacy, resilience, cost management and enterprise integration.

Person Specification

• Enterprise thinker who treats data as a product and a controlled asset, not simply a technology platform.
• Able to challenge local optimisation and drive reuse, standardisation and clear ownership across organisational boundaries.
• Commercially aware, evidence-led and comfortable making investment and prioritisation decisions.
• Strong communicator who can translate between executives, data specialists, engineers and control functions.
• Collaborative across business domains and able to create shared ownership of data outcomes.
• Inclusive leader who develops talent and builds a culture of quality and accountability.

Hours of Work:

8.30am – 5.30pm / 40 hours per week, Monday to Friday