Python Developer - Distributed Systems - Hedge Fund

London | Multi-Strategy Hedge Fund | Permanent The Client Tempest Vane Partners has partnered with a well-capitalised, multi-strategy hedge fund seeking a talented Quant Data Distributed Engineer to join a sophisticated engineering function in London. The Role This opportunity sits within a technology‑first organisation where data infrastructure is central to the performance of systematic investment strategies. The successful candidate will work on highly scalable, distributed data systems that underpin quantitative research, signal generation, and live trading operations. The position offers significant exposure to cloud‑native engineering, systematic data pipelines, and large‑scale distributed architecture within a fast‑moving and intellectually rigorous environment. The Opportunity The incoming engineer will play a key role in the design, development, and scaling of the data infrastructure that powers the firm's systematic strategies. Working closely with quantitative researchers, data scientists, and platform engineers, the role will focus on data reliability, low‑latency delivery, and the continued evolution of the firm's distributed systems capability. Core responsibilities will include: Engineering and maintaining large‑scale distributed data systems supporting systematic investment strategies Designing and optimising data pipelines handling high‑frequency, time‑series, and alternative data sets Driving cloud infrastructure development and best practices across AWS environments Supporting container orchestration and platform reliability through Kubernetes Collaborating with quant researchers to ensure high‑quality, performant data availability Contributing to automation, observability, and operational efficiency across the data platform Partnering with engineering and research teams on platform improvements and strategic delivery Candidate Requirements Strong Python engineering capability, with a focus on clean, production‑grade code Hands‑on AWS experience across relevant services including S3, EC2, Lambda, Redshift, or Glue Deep understanding of Kubernetes and container‑based infrastructure Experience working with systematic or quantitative data environments, including tick data, time‑series, or alternative data Proficiency in at least one additional object‑oriented language such as C++, Java, or Scala Familiarity with distributed systems design and data engineering principles Exposure to workflow or streaming technologies such as Airflow or Kafka is advantageous Strong analytical and troubleshooting capability with an engineering‑first mindset Profile This role would suit an engineer who thrives at the intersection of data engineering and quantitative finance. The team is looking for individuals who are intellectually curious, highly collaborative, and motivated by solving complex, high‑impact problems at scale. The environment rewards technical ownership, precision, and continuous improvement, making it well‑suited to engineers who enjoy working close to live trading and systematic research.

For further information or a confidential discussion, please apply directly via Tempest Vane Partners. #J-18808-Ljbffr