London | Contract or Permanent | Immediate Start

We are working with a market-neutral equity fund that is looking to hire an experienced Quantitative Developer or Data Engineer to support a significant rebuild of its technology and research infrastructure.

The fund operates a fully systematic investment process, and this role will sit at the intersection of data engineering, quantitative research and investment technology.

The initial focus will be on rebuilding and improving the fund’s data infrastructure, including data ingestion, processing and vendor integration. The role will then extend into quantitative development, helping transform financial data into research-ready datasets, investment signals and tools used within the systematic investment process.

This could suit someone from a front-office data engineering, quantitative development or systematic investment technology background. The fund is open to both contractors and permanent hires, although the ability to start quickly is important.

Key responsibilities

1. Build and maintain robust ETL processes and financial data pipelines
2. Manage the ingestion, cleaning and processing of large financial datasets
3. Work with external data vendors and maintain accurate security and symbology mapping
4. Develop cloud-based quantitative research and production infrastructure
5. Support the development and implementation of systematic equity signals
6. Work closely with the investment team to turn research ideas into scalable tools and processes
7. Improve testing, deployment and engineering standards across the platform
8. Contribute to the wider rebuild of the fund’s technology stack

Required experience

1. A minimum of five years’ relevant experience, ideally closer to eight or more
2. Strong Python development skills
3. Experience building and maintaining ETLs and data pipelines
4. Strong knowledge of Microsoft Azure
5. Experience with Docker and Azure Kubernetes
6. Experience using Apache Airflow
7. GitHub repositories and CI/CD using GitHub Actions
8. Experience working with cloud-based data and research platforms
9. Familiarity with financial data and financial data vendors
10. Previous experience within equities is strongly preferred

Experience with any of the following would be particularly relevant:

1. S&P Xpressfeed and Snowflake
2. Bloomberg
3. MSCI Barra
4. Databricks
5. Systematic equity research or factor models
6. OpenAI large language models
7. Claude Code

The ideal candidate will have worked in a front-office investment environment and will be comfortable operating across both data engineering and quantitative development. Someone who has built research platforms, data pipelines, feature libraries or signal-generation infrastructure within an asset manager, hedge fund or systematic investment team would be particularly well suited.

The position is available on either a contract or permanent basis and is expected to start as soon as possible.

Applicants must already have the right to work in the UK, as sponsorship is not available

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