About this role
Salary: £65,000 - 105,000 per year
Requirements: Experience building and operating production data pipelines rather than one-off scripts or analysis tooling.Strong Python development skills, with experience building performant, maintainable applications.Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect.Understanding of retries, dependency management, idempotency, backfills, and operational recovery.Experience with analytical or columnar databases such as ClickHouse or similar technologies.Knowledge of partitioning, materialised views, and query optimisation techniques.Experience with numerical and data processing libraries including NumPy, pandas, Polars, or Arrow.Understanding of performance optimisation, memory usage, multiprocessing, or asynchronous Python. Responsibilities: Develop and maintain production data pipelines supporting our risk analytics platforms.Build reliable, recoverable, and observable data workflows.Improve the quality, freshness, and completeness of critical risk data.Engineer performant Python applications for data processing and transformation.Optimise large-scale analytical data stores and query performance.Contribute to monitoring, alerting, and operational reliability across our data services. Technologies: AirflowClickHousePythonnumpypandas More:
We are supporting a global quantitative investment manager whose risk platforms rely on high-quality, real-time data. This role sits within our engineering team responsible for the ingestion, transformation, storage, and delivery of market, position, and reference data into critical risk systems. The position is based in London and offers a competitive salary plus bonus. This is a hands-on software engineering opportunity for someone who enjoys building production-grade data systems and cares as much about data reliability as they do about clean code.
last updated 29 week of 2026