Python Data Engineer

Huxley Associates; Greater London; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading multi-strategy hedge fund is seeking a highly skilled Python Data Engineer in London to focus on building and optimizing data infrastructure. The role demands strong Python skills, AWS experience, and a solid understanding of financial market data. Candidates will develop scalable ETL pipelines, ensure data quality, and collaborate with trading teams. This position offers a competitive salary, performance-based bonuses, and a hybrid work environment, requiring 2 days on-site.

Benefits

Competitive compensation

Performance-based bonus

Collaborative work culture

Qualifications

• Strong proficiency in Python and ETL development.
• Hands-on experience with AWS and Databricks.
• Solid understanding of financial market data, particularly time-series.

Responsibilities

• Develop and maintain scalable Python-based ETL pipelines.
• Design and manage cloud-based data lake solutions (AWS, Databricks).
• Implement data quality and cleansing routines for financial data.
• Collaborate with teams to deliver tailored data solutions.

Skills

Python proficiency (pandas, NumPy, PySpark)

ETL development

AWS services experience (S3, Glue, Lambda)

Financial market data understanding

Education

Degree in Computer Science, Engineering, or related field

Tools

Databricks

SQL and relational databases

Docker

Kubernetes

Job description

Python Data Engineer - Multi-Strategy Hedge Fund

Location : London | Hybrid : 2 days per week on-site | Type : Full-time

About the Role

A leading multi-strategy hedge fund is seeking a highly skilled Python Data Engineer to join its technology and data team. This is a hands‑on role focused on building and optimising data infrastructure that powers quantitative research, trading strategies, and risk management.

Key Responsibilities

Develop and maintain scalable Python‑based ETL pipelines for ingesting and transforming market data from multiple sources.

Design and manage cloud‑based data lake solutions (AWS, Databricks) for large volumes of structured and unstructured data.

Implement rigorous data quality, validation, and cleansing routines to ensure accuracy of financial time‑series data.

Optimize workflows for low latency and high throughput, critical for trading and research.

Collaborate with portfolio managers, quantitative researchers, and traders to deliver tailored data solutions for modeling and strategy development.

Contribute to the design and implementation of the firm’s security master database.

Analyse datasets to extract actionable insights for trading and risk management.

Document system architecture, data flows, and technical processes for transparency and reproducibility.

Requirements

Strong proficiency in Python (pandas, NumPy, PySpark) and ETL development.

Hands‑on experience with AWS services (S3, Glue, Lambda) and Databricks.

Solid understanding of financial market data, particularly time‑series.

Knowledge of data quality frameworks and performance optimisation techniques.

Degree in Computer Science, Engineering, or related field.

Preferred Skills

SQL and relational database design experience.

Exposure to quantitative finance or trading environments.

Familiarity with containerisation and orchestration (Docker, Kubernetes).

What We Offer

Competitive compensation and performance‑based bonus.

Hybrid working model : 2 days per week on‑site in London.

Opportunity to work on mission‑critical data systems for a global hedge fund.

Collaborative, high‑performance culture with direct exposure to front‑office teamsTo Avoid Disappointment, Apply Now!

To find out more about Huxley, please visit

Huxley, a trading division of SThree Partnership LLP is acting as an Employment Business in relation to this vacancy | Registered office | 8 Bishopsgate, London, EC2N 4BQ, United Kingdom | Partnership Number | OC(phone number removed) England and Wales