At a Glance
- Tasks: Build data systems and pipelines to enhance energy trading analytics.
- Company: Join Castleton Commodities International, a leader in energy trading tech.
- Benefits: Enjoy competitive pay, flexible work options, and growth opportunities.
- Other info: Collaborative team environment with global impact.
- Why this job: Shape the future of energy trading with innovative data solutions.
- Qualifications: Experience in data engineering and a passion for analytics.
The predicted salary is between 60000 - 80000 £ per year.
Castleton Commodities International (CCI) is redefining how data and technology shape the future of energy trading.
The Data Science & Technology team builds data systems and open‑source tools that empower front‑office teams to forecast prices, manage risk, and understand market dynamics.
The Data Engineer role focuses on data ingestion pipelines, data management platforms, and collaborating with global commercial investing teams to expand data‑driven analytics across the trading business.
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Data Engineer, Energy Trading Tech & Analytics in London employer: Castleton Commodities International
As a Contract Negotiator at our company, you will thrive in a dynamic work environment that values collaboration and innovation within the energy sector. We offer competitive benefits, a supportive culture that encourages professional growth, and opportunities to engage with industry-leading experts. Located in a vibrant area, our workplace fosters a sense of community and commitment to excellence, making it an ideal place for those seeking meaningful and rewarding employment.
Contact Details:
Castleton Commodities International Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer, Energy Trading Tech & Analytics in London
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We think you need these skills to ace Data Engineer, Energy Trading Tech & Analytics in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
