Join a small data team at a London hedge fund, transforming raw third-party market data into usable insights for traders and quants. Day to day you build and improve data pipelines, dictionaries and quality processes using Python (or C#), SQL, Apache Spark and Azure Databricks.
In this role you will join a small data team in a London hedge fund to transform raw data from multiple sources into usable insights for traders and quants. You will build and improve data systems, dictionaries and processes, ensuring data quality and accessibility across platforms. You’ll collaborate with technology teams to stay current with data tooling and industry trends, delivering timely data-driven insights to front-office users. This position offers a path to influence how data supports trading decisions and research. You will work in a dynamic, finance-focused environment with strong career development support.
Pay / Benefits
Salary up to 160k
Significant bonus potential
Fund performance share
Personal training budget and mentoring
Family-friendly benefits including backup childcare and elder care
Private healthcare and wellness activities
Responsibilities
Transform raw data from multiple third-party sources into usable insights for trading desks and quants
Combine and transform data to support analysis and visualisation
Interrogate vendor data endpoints to source and analyse data
Ensure data consistency, completeness and accuracy across platforms
Develop data dictionaries and documentation
Collaborate with technology teams to enhance data systems and processes
Stay updated with industry trends and emerging data tooling
Key requirements
First class degree in a STEM discipline from a top tier university
Experience in a Data Engineer role within hedge fund or investment banking
Strong programming skills in Python or C# and SQL
Experience with version control and collaborative codebases
Experience with modern data tools including Apache Spark and Azure Databricks
Solid knowledge of data management principles and best practices
Experience with data analysis and data visualization techniques
Ability to explain complex data to front-office traders
Exposure to data sources like Bloomberg (BBG), Markit, Refinitiv (preferred)