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Lead Data Engineer

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Lead Data Engineer
If you enjoy building data platforms from the ground up rather than maintaining someone else's, this is an opportunity to have a genuine influence on both the technology and the direction of the business.
You'll be joining an early-stage AI company with a product already proving itself in the market. As the first senior data engineering hire, you'll define the data architecture, shape engineering standards and build the foundations that support AI at scale.
What's in it for you?
- Competitive salary plus meaningful equity
- Own the data strategy and architecture from day one
- Work directly with experienced founders and a small engineering team
- Build modern data infrastructure that powers AI products
- Influence technical decisions and future hiring as the team grows
- Join early enough for your work to have a lasting impact
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.
The role
This is a hands-on leadership role where you'll design and build the data platform behind an AI-driven product. From scalable pipelines and real-time data processing to vector databases and machine learning workflows, you'll be responsible for creating reliable, high-performance infrastructure that enables the platform to grow.
What you'll be doing
- Design and build scalable data pipelines and modern data infrastructure
- Develop batch and real-time processing systems that support AI applications
- Build and optimise data storage, retrieval, and vector search capabilities
- Improve platform reliability, security, monitoring, and data quality
- Partner with engineering teams to support machine learning and product development
- Contribute to long-term technical architecture and engineering strategy
- Help build and mentor the future data engineering function as the company grows


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What you'll bring
- Strong experience building scalable data platforms or backend systems
- Expertise designing data pipelines and distributed data architectures
- Excellent Python development skills
- Experience working with relational and NoSQL databases
- Knowledge of modern data infrastructure and cloud technologies
- Strong architectural thinking and a practical approach to solving complex problems
- A genuine enthusiasm for building systems from scratch and taking ownership
If you're looking for a role where you'll shape the technical foundations of an AI business from the beginning, this is one you'll want to explore.
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