Bourne Search Ltd
Data Engineer

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Senior Data Engineer | Trading Analytics | London, 3 days on site
A London Trading firm is building a trading data platform from scratch, in house, on open source. Spark, Kafka, Polaris, Ranger, Airflow, MinIO. This is the person who builds it.
Why now
The analytics function is running on legacy warehouses that were never built for the volume or the velocity of trading data. They are consolidating them into a single lakehouse handling streaming and batch together, and building it in house rather than buying it. A Principal Data Engineer is being hired alongside this role to own the architecture. You will be the one turning that design into a working platform.
What you would do
- Build ingestion pipelines for both streaming and batch sources
- Write the Spark jobs that clean, transform and land data in the lakehouse
- Build and own Airflow orchestration
- Work on cataloguing and access control with Polaris and Ranger
- Help migrate data off the legacy warehouses and retire them
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.
Start with a chat, not a search bar
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.
See breakdownIt searches the market for you
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.
What we need
- Strong SQL and Python. These are the working languages of the platform.
- Real experience building production data pipelines, not just maintaining them
- Spark, and some exposure to Kafka or another streaming technology
- Comfort with infrastructure that someone runs themselves rather than only managed cloud services
- Financial markets background, any asset class. Commodities not required.
Useful, not essential
- Java or another JVM language
- Hadoop, HDFS, S3-compatible object storage, open table formats
- Kubernetes, Terraform, CI/CD
Who this suits
Someone two to six years into a data engineering career who wants to build a platform from the ground up rather than add features to one that already exists. You will be closer to the metal here than in most roles at this level, and you will learn more in the first year than in three years of pipeline maintenance somewhere else. If you want a title and a team, the Principal role is the one to look at instead.


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The honest version
It is 3 days a week on site in London. Some of the estate is on premise and some of what you inherit is legacy that needs retiring. In exchange you get to build a modern lakehouse at, on open source, with someone senior to learn from.
Process
Three stages: an introductory call, a technical discussion built around real scenarios rather than a timed coding test, and a conversation with the CTO. Moving quickly, filling before year end.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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