Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Engineer

EDF Trading Ltd
City of London
4 weeks ago
Create job alert

Main responsibilities This role bridges hands on data engineering with data governance. You will design and operate robust data pipelines and models with a focus on embedding governance by design - capturing metadata and lineage, enforcing access controls and data quality, and ensuring our catalogue and stewardship model reflect the reality of how data flows across EDF Trading.Support the establishment and management of data products by identifying critical data, gathering and documenting data requirements, and embedding data risk and control management within data flows. Collaborate with data owners, stewards, and business teams to ensure data assets are trusted, well-documented, and fit for purpose. Required Skills and ExperienceStrong experience in data engineering: ETL/ELT, data modelling, and data analytics and programming languages (e.g., Python, SQL, Alteryx).Experience with data catalogues (e.g. Collibra, Alation) and / or metadata management generally.Experience with data analysis and data modelling (hands-on experience with conceptual, logical and physical data models)Experience implementing data quality controls and issue management processes within data pipelines. Experience with data visualisation tools (Power BI, Tableau).Strong stakeholder engagement skills, including running workshops and presenting to business users. Desirable Skills and ExperienceExperience in the energy trading sector or similarly data-rich environments.Experience with data platforms and tools (e.g., Azure, Databricks, MSSQL, Kafka). Hands-on experience developing conceptual, logical, and physical data models. Ability to multitask, switch focus and prioritise own tasks Strong communication and interpersonal skillsAbility to fully participate in a multi-faceted team environmentWe are committed to equipping our employees with the tools that will enable them to fulfil their job to the highest standard. To that end we offer a wide range of technical and personal development courses both in-house and through third-party providers."It is a fast-paced and dynamic working environment where each day is interesting and challenging. There’s also an incredible pool of talent and skills within EDFT. I’m continuously learning from my colleagues.""There is no ‘typical’ day. I work on a wide range of compensation, benefit and mobility projects throughout the year. One thing’s for sure though, I’ll have my head in a spreadsheet at some point."
#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer – SC Cleared

Senior Data Engineer/ Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.