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

Apply Now

Senior Data Engineer | Commodities & Energy Trading | Greenfield Next-Gen Lakehouse | Up to £89K + Bonus + Benefits

VirtueTech Recruitment Group
London
1 day ago
Create job alert

Senior Data Engineer | Commodities & Energy Trading | Greenfield Next-Gen Lakehouse | Up to £89K + Bonus + Benefits


Data Engineer required for an Energy and commodities trading house, which is one of the worlds largest and most diverse general trading companies. Working with different types of commodities and a fast growing business.


Senior Data Engineer needed for the core engineering team. As a senior member of the Data Engineering team, you’ll play a key role in shaping and delivering scalable data solutions that support both day-to-day operations and long-term business growth. Focusing on building and maintaining their data platform’s. In this hands on role, you’ll guide a small team of data engineers and help shape a data platform that’s reliable, easy to use, and fit for everything from day-to-day business decisions to regulatory reporting.


As a Senior Data Engineer, you will be pivotal and help guide the build a modern, next-generation core engineering platform—a greenfield enterprise foundation that will sit at the centre of all future initiatives. This platform will act as the gateway for business and trading teams, giving them access to centralised, enterprise-grade capabilities that enable faster, smarter, and more efficient product development.


In this Senior Data Engineer role, you'll play a pivotal role in designing, building, and maintaining modern lakehouse-based data platforms. Working closely with the Head of Core Engineering and teams across the business. You’ll help shape the organisation’s data strategy and ensure the platform aligns with long-term objectives.


In this Senior Data Engineering role, you’ll design, develop, and maintain data platforms using technologies such as Snowflake, Databricks, Synapse/Fabric, and PySpark, ensuring the scalability, security, and performance of all data systems. As the Senior Data Engineer your role will be to include establishing and championing best practices for data engineering while creating development environments that support efficient and reliable data processing.


🔍 Key Responsibilities of the Senior Data Engineer:

  • Solid grasp of modern data engineering concepts and workflows.
  • Strong Databricks experience
  • Familiarity with Azure and related DevOps tools.
  • Strong Python programming capability.
  • Knowledge of data orchestration, pipeline development, and data modelling.
  • Background in connecting data platforms with visualisation tools like Power BI and Tableau.


💼 Details for the Senior Data Engineer:

  • Salary: Up to £89,000 per annum + Bonus & Benefits
  • Location: London (Hybrid – 3 days in the office per week)


If you’re looking to be part of a one of the leading energy and commodities trading companies, working with the core engineering department and building and maintaining data platforms, we’d love to hear from you.


Senior Data Engineer | Commodities & Energy Trading | Greenfield Next-Gen Lakehouse | Up to £89K + Bonus + Benefits

Related Jobs

View all jobs

Senior Data Engineer | Commodities & Energy Trading | ClickHouse-Centric Data Platform | Next-Gen Lakehouse | Python, SQL | Up to £89K + Bonus + Benefits

Senior Data Engineer - Databricks | £110,000 + Strong Bonus and Benefits - Commodities

Senior Machine Learning Research Scientist

Senior Machine Learning Research Scientist

Senior Machine Learning Research Scientist

Senior Machine Learning Research 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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

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.