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Radley James

Data Engineer

London
£140k – £200k/yr
Posted about 13 hours ago
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Data Engineer – Quantitative Data Platform

Location: London

Compensation: Up to £200,000 base + performance bonus

I’m working with a leading investment firm in London that is looking to hire an experienced Data Engineer to help build and scale a high-performance data platform supporting quantitative investment teams.

This is a highly technical engineering role focused on large-scale data infrastructure, backtesting, and research workloads. You’ll be working with petabyte-scale datasets and partnering closely with quantitative engineers and researchers.

What you’ll be working on:

  • Building and scaling data infrastructure for backtesting and other data-intensive applications
  • Developing ingestion and ETL pipelines operating across petabyte-scale datasets
  • Solving challenges around data quality, storage, backfills, and high-performance data consumption
  • Designing batch and streaming data architectures
  • Working closely with quantitative researchers and engineering teams
  • Improving the scalability, reliability, and performance of distributed data systems

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.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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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It 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.

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Strong

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.

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Strong

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’re looking for:

  • 5+ years of experience in data-intensive engineering
  • Strong SQL and database expertise, particularly with large-scale or time-series datasets
  • Strong programming skills in Python, Rust, and/or C++
  • Experience with tools such as Pandas, Polars, Dask, or PySpark
  • Experience building data platforms, ETL systems, data lakes, warehouses, or lakehouse architectures
  • Knowledge of Parquet, Arrow, or similar columnar formats
  • Experience with distributed systems technologies such as Kafka and Redis
  • Strong understanding of performance optimization and debugging

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Nice to have:

  • ClickHouse, Snowflake, or similar technologies
  • Financial markets / quantitative investment experience
  • REST API development
  • Prometheus, Grafana, or Sentry

Why join?

You’ll have the opportunity to work on genuinely large-scale data engineering problems where performance and reliability matter, while building infrastructure used directly by quantitative investment teams.

Compensation: £140,000 to £200,000 base + bonus

Location: London

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Skills

SQL
Python
Rust
C++
Pandas
Polars
Dask
PySpark
ETL
Distributed Systems
Kafka
Redis
Data Lakehouse
Parquet
Arrow
Performance Optimisation

Location

London, England, United Kingdom

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