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Data Engineer

Radley James· London Area, United Kingdom· £140,000–£200,000/yr
Posted 18 Sept 2026 · Added 4 Sept 2026, 09:00
Radley James4.0 (4)Recruitment agencyfounded 2009
AI summary

You will work with SQL, Python, Rust/C++, Pandas, Polars, Dask, PySpark, Parquet, Arrow, Kafka, Redis, plus ClickHouse, Snowflake, REST APIs, Prometheus, Grafana, and Sentry. You’ll build and scale data infrastructure, ETL pipelines, and batch/streaming architectures for a quantitative investment firm’s petabyte-scale backtesting and research workloads, partnering with quantitative engineers and researchers.

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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

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 optimisation and debugging

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