Senior Data Engineer - $8 Billion Hedge Fund

JR United Kingdom; London; Hybrid; GBP 80,000 - 120,000; Full time

Job summary

A leading hedge fund in London seeks a Senior Data Engineer to enhance its data infrastructure. This high-impact role involves building scalable data pipelines while collaborating closely with quantitative teams. Candidates should have over 5 years of experience in data engineering with strong skills in Python and SQL.

Qualifications

• 5+ years in data engineering.
• Strong Python and data wrangling libraries.
• Expert SQL skills and solid RDBMS understanding.

Responsibilities

• Build scalable data pipelines and platforms.
• Collaborate with quants and portfolio managers.
• Ingestion, transformation, and delivery of diverse datasets.

Skills

Python

SQL

Data wrangling

Cloud-based data solutions

Git

Docker

CI/CD pipelines

APIs

dbt

Snowflake

Kafka

Airflow

Job description

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Senior Data Engineer - $8 Billion Hedge Fund, london

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Client:

Radley James

Location:

london, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

3

Posted:

26.06.2025

Expiry Date:

10.08.2025

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Job Description:

Senior Data Engineer - Hedge Fund - London

Company Overview

A leading London-based systematic hedge fund managing over $8 billion in client assets. Technology is core to its operations, with a strong focus on data-driven strategies. The team is currently overhauling its data infrastructure to better support quant research and trading.

Role Overview

Join a lean, high-impact Data Engineering team responsible for the ingestion, transformation, and delivery of diverse datasets—from tick and time series to reference and alternative data. You’ll build modern, scalable data pipelines and platforms, support the strategic tech stack, and collaborate closely with quants and portfolio managers. This is a hands-on role with full ownership across the development lifecycle.

Qualifications

• 5+ years in data engineering
• Strong Python and data wrangling libraries
• Expert SQL skills and solid RDBMS understanding
• Experience with cloud-based data solutions (e.g. serverless ETL, data warehouses)
• Familiarity with Git, Docker, CI/CD pipelines, testing and monitoring
• Clear communicator, comfortable with cross-functional teams
• APIs from major financial data providers
• dbt, Snowflake
• Kafka, Airflow
• Java feedhandler support
• Migration of legacy systems (e.g. MATLAB)

This position offers a competitive compensation package and hybrid working model.