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Data Engineer | London (Hybrid) | £5BN Asset Management Firm
About the Opportunity
We are collaborating with a London-based investment firm with strong ties to hedge funds and institutional finance. They prioritise substance over spectacle—running serious capital and seeking serious, reliable engineering to match.
We are seeking a data engineer with solid fundamentals who can:
- Own and maintain production systems
- Enhance reliability and data freshness
- Introduce innovative capabilities
- Adapt priorities to evolving business needs
This is not a transactional "build what you’re told" role. Instead, we need a self-motivated, proactive engineer able to:
- Identify business challenges through data
- Map data architectures
- Drive end-to-end solutions with collaboration across teams
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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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
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.
Key Responsibilities
- Solve business challenges with data—work with Ops, Research, and Investment Teams to find pain points and build practical, scalable solutions, not just process tickets.
- Upgrade the data platform:
- Optimise ingestion, transformation, storage, and serving
- Enhance observability and reliability
- Reduce latency and stale data—improve alerting to avoid silent failures
- Design and maintain production systems with an emphasis on efficiency
Technical Stack
✔ SQL (feature-rich usage) ✔ Python ✔ AWS (full-flow applications) ✔ Terraform
What We’re Looking For
Technical Experience & Skills
- Proven Data Engineering or relevant role experience
- Ownership mentality: Ready to identify pain points and deliver end-to-end data solutions, not just follow specs
- Python & SQL mastery—comfortable with complex, mission-critical workflows
- AWS ecosystem experience—sauce expertise on cloud services
- Familiarity with DevOps or CI/CD practices (e.g., Terraform)


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Soft Skills & Approach
- Collaborative communicator—bridges technical and non-technical stakeholders
- Proactive mindset—figures out unmet needs before they’re formally requested
- Data-driven problem-solver
Compensation
- Very competitive salary and performance-based bonuses
Get in touch if you’d like to be part of this exciting challenge!
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Jessica, London
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