Python Data Engineer - Hedgefund

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

Job summary

A leading multi-strategy hedge fund based in London is looking for a skilled Python Data Engineer to optimize data infrastructure that supports quantitative research and trading strategies. Your responsibilities include managing ETL pipelines, designing cloud-based data solutions, and ensuring data quality for financial analysis. This full-time role offers a hybrid work model, competitive compensation, and a chance to collaborate with high-performance teams directly involved in trading operations.

Benefits

Competitive compensation

Performance-based bonus

Collaborative culture

Qualifications

• Strong proficiency in Python and ETL development.
• Hands-on experience with AWS services.
• Solid understanding of financial market data.

Responsibilities

• Develop and maintain scalable Python-based ETL pipelines.
• Design and manage cloud-based data lake solutions.
• Implement rigorous data quality routines.

Skills

Python (pandas, NumPy, PySpark)

ETL development

AWS services (S3, Glue, Lambda)

Data quality frameworks

Financial market data

Education

Degree in Computer Science, Engineering, or related field

Tools

Databricks

SQL

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 teams.

To Avoid Disappointment, Apply Now!

To find out more about Huxley, please visit (url removed)