CipherTek Recruitment
Senior Data Engineer

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🔥 Senior / Lead Data Engineer – Databricks / Spark (High-Performance Platform)
£850 p/d OUTSIDE IR35 (higher for Lead)
12-month rolling (multi-year programme)
1 day/week – St Paul’s, London
We’re hiring a Senior & Lead Data Engineer to build a Databricks lakehouse platform in a high-performance, business-critical Front office Risk trading environment.
This is a hands-on engineering role focused on building and optimising large-scale distributed data systems.
This is a highly technical team operating at scale, we’re looking for engineers with deep data engineering expertise, strong low-level Spark knowledge, and experience building high-performance systems using modern Databricks and AI-driven platforms.
This is working for a Front office Risk Data team, so you MUST have experience working closely with Front/middle office users and have good domain knowledge covering Risk and derivatives.
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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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
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.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What you’ll do
- Build and optimise Spark pipelines on Databricks
- Develop a lakehouse platform (Medallion architecture)
- Own data modelling, architecture, and pipeline design
- Work with large-scale data (TB–PB)
- Drive performance, scalability, and reliability in production
What we’re looking for
- Strong experience running Spark workloads in production
- Proven ability to optimise Spark at scale (Tb/PB datasets)
- Solid Python (Scala beneficial, not essential)
- Experience with data modelling and lakehouse architecture
- Ability to debug and improve performance in distributed systems


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Important
- Must have recent, hands-on Spark experience
- Databricks strongly preferred (not essential if Spark depth is very strong)
- Experience supporting AI/ML or advanced analytics platforms is a big plus
- Financial services / trading exposure
- Experience in performance-critical environments
Not a fit if
- Primarily BI / reporting focused
- Spark used only at small scale or outside production
- No experience with performance optimisation in distributed systems
Stack
- Databricks (Azure)
- Spark
- Delta Lake
- Python (+ Scala optional)
Bottom line
We’re looking for engineers who can design, build, and optimise Spark-based systems at scale and operate effectively in a performance-critical environment from day one.
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