Responsibilities

Design, develop and enhance Python-based data services used by front-office and quantitative teams.
Build scalable data pipelines and services to ingest, transform and deliver high-quality datasets.
Develop robust data validation frameworks to improve the accuracy and reliability of derived data.
Work closely with quantitative researchers, traders and engineering teams to understand data requirements and expected outputs.
Cleanse, filter and validate raw datasets to ensure data quality before they are consumed by downstream users and applications.
Support the centralisation of data services, reducing duplication and improving consistency across multiple data sources.
Contribute to the design and implementation of scalable, reusable data architecture rather than tactical point solutions.
Build and maintain APIs and data platforms capable of serving large-scale financial datasets.
Take ownership of solutio...