Data Platform Software Engineer
Job Description
[Up to c. £180k Comp Package | Hybrid Working - 4 Days in Office]
Role Overview
We’re supporting a world-leading quantitative trading firm with a reputation for advanced machine learning, large-scale computing, and engineering excellence. They’re expanding their Data Platform function, which underpins critical trading and research activity across the business. This team’s mission is to design and maintain a unified, highly reliable repository of market data - from fundamentals and corporate actions to index membership - ensuring internal teams can access accurate, consistent, and well-structured datasets. You’ll build and optimise ingestion pipelines, design frameworks to process high-volume data, and explore new approaches to error detection, data quality, and integration. With direct impact on how billions are traded daily, this role combines low-level software engineering with large-scale data problem solving, offering exposure to distributed systems, advanced data processing, and applied statistics...
Key Responsibilities
- Engineer and maintain automated pipelines to ingest and process high-value third-party datasets
- Develop scalable systems for data normalisation, storage, and distribution across the firm
- Proactively identify and address data quality issues through statistical modelling, regression testing, and algorithmic error detection
- Collaborate closely with researchers, technologists, and trading teams to align data capabilities with business needs
- Investigate new datasets and patterns within existing data to expand the platform’s value
- Ensure all solutions are robust, reliable, and highly automated, reducing manual intervention where possible
- Produce technical documentation and communicate updates to internal stakeholders clearly and effectively
What You’ll Bring...
- Strong programming ability in at least one statically typed language (e.g. Java, C++, Go); familiarity with Go or willingness to adopt it in production settings
- 3+ years experience building and running distributed systems in production environments
- Comfort with data analysis and statistics, including regression techniques and error modelling; exposure to machine learning methods preferred
- Hands-on experience using and administering relational databases
- Proactive approach to problem solving with the ability to work independently in a high-autonomy environment
- Strong communication skills, able to partner effectively with stakeholders across research, engineering, and trading teams
- (Preferred) Background in financial data or markets
...
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