Job Description
Python Distributed Systems Engineer – Quantitative Trading Technology
Location: London
Compensation: Circa £250,000 Total Compensation (Base + Bonus)
Company:
I’m currently working with a global-leading multi-strat investment firm operating at scale — thousands of strategies, millions of data points per second, sitting at the intersection of technology and quantitative research. They build cutting-edge distributed systems that power real-time trading, risk management, and data analytics across global markets.
The Role:
Currently looking for an exceptional Python Engineer to design, implement, and optimize distributed systems that underpin the global quantitative trading platform.
You’ll work alongside world-class developers, quantitative researchers, and infrastructure experts to build low-latency, fault-tolerant, and highly scalable systems. This is an opportunity to work on projects where milliseconds and megabytes matter — and where your code directly contributes to business performance.
What You’ll Do
* Architect and implement distributed data pipelines and compute frameworks in Python
* Build services that handle high-throughput event streams and large-scale time-series data
* Collaborate with quant teams to integrate new datasets, models, and analytics tools
* Optimize performance for latency, throughput, and reliability
* Contribute to the continuous evolution of our engineering culture — automation, CI/CD, observability, testing
What We’re Looking For
* 4+ years of experience in Python (asyncio, multiprocessing, FastAPI, or similar frameworks)
* Solid understanding of distributed systems concepts: messaging, consensus, data partitioning, fault tolerance
* Experience with technologies such as Kafka, Redis, gRPC, Kubernetes, Ray, or Dask
* Strong background in Linux environments and performance tuning
* A passion for clean code, automation, and technical excellence
* Exposure to financial data, trading systems, or high-frequency environments is a strong plus
Please contact daniel.mclagan@stanfordblack.com for more information.
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