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Senior Data Engineer

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Senior Data Engineer | AI Startup | Camden | Hybrid (3-4 onsite)
I’m currently recruiting for a Senior Data Engineer to join a fast-growing AI-driven technology business transforming how hospitality businesses operate. This is a hands-on, high-ownership role where you’ll play a key part in building and scaling the data platform behind the product.
The company has built an AI-powered platform that uses data to forecast demand, optimise staffing and automate rota planning, and has already surpassed £1m ARR within its first 10 months.
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
- Design, build & maintain ETL/ELT data pipelines
- Work with Python & complex SQL
- Deploy and support ML systems in production
- Work with AWS - S3, Redshift, RDS, Athena, SageMaker & Lambda
- Build integrations with internal & external systems
- Improve reliability, monitoring, scalability & performance
- Work closely with Data Scientists, Engineers & Product teams
- Support and mentor junior engineers


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Requirements
- Strong Data Engineering fundamentals
- Production-quality Python & SQL
- Experience with ML systems in production
- AWS/cloud & DevOps experience
- A strong ownership mindset and willingness to get hands-on
If you're a Data Engineer who wants genuine ownership and the opportunity to build data/ML infrastructure at a rapidly scaling AI company, happy to connect!
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