X4 Technology
Data Engineer (Energy Trading)

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Role: Data Engineer
Programme: Trading data transformation Industry: Energy Trading Location: London (Hybrid) Contract: Initial 6-month contract (long-term transformation programme) Rate: £650-700/day (Inside IR35)
X4 Technology are partnered with a major energy trading organisation on a strategic programme to unlock the power of their data across Trading, driving sharper decision-making and new cross-commodity trading opportunities.
Key focuses are pulling analysis out of Excel, unlocking modern visualisation tools and building out a proper Databricks-powered data platform to give trading desks real, near-term value from their data.
Joining as Data Engineer, you'll own data products end-to-end - from design and build through to deployment and live support - combining serious data engineering experience with strong backend/API development.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Responsibilities for the Data Engineer
- Design, build and maintain scalable data pipelines and data products using Python, PySpark, Databricks and SQL Server
- Develop and support modern REST APIs and backend services using FastAPI - a genuine hands-on API-building role, not just pipelines
- Own engineering end-to-end across the full SDLC - design, build, test, deploy, monitor and support - working closely with stakeholders, product owners, architects and engineers to turn requirements into robust solutions
- Build and maintain CI/CD pipelines, automated testing and release automation via GitHub Actions, plus containerised deployments using Docker and Kubernetes
- Champion engineering best practice - code reviews, automated testing, security, observability and operational excellence


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Requirements for the Data Engineer
- Strong hands-on Python, PySpark, Databricks and SQL Server experience
- Strong, proven FastAPI experience - this is essential, not a nice-to-have
- Solid Azure cloud experience, plus Docker, Kubernetes and GitOps
- Strong understanding of data architecture, data modelling and data governance principles
- Excellent stakeholder engagement - comfortable with both technical and non-technical audiences
A brilliant opportunity to build modern, cloud-native data products at the heart of a major trading business's data transformation - full ownership from design to production, with real influence over how the platform evolves. Please apply now for immediate consideration.
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