Senior Data Engineer | Commodities & Energy Trading | Greenfield Next-Gen Lakehouse | Up to £110K + Bonus + Benefits

VirtueTech Recruitment Group
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Vice President, Lead Data Engineer

Data Engineer - Modern Data & AI Platforms

Senior Data Engineer (Financial Services)

Up to £200,000 base + bonuses - Data Engineering Lead

Up to £200,000 base + bonuses - Data Engineering Lead

Senior Data Scientist

Senior Data Engineer | Commodities & Energy Trading | Greenfield Next-Gen Lakehouse | Up to £110K + 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 £110,000 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 £110K + Bonus + Benefits

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.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.