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# Software Engineer, Macro Quant Analytics Technology

- **Company:** Peoplewe
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £200,000.0 - £300,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), C Sharp (Programming Language), C++ (Programming Language), Cloud Computing, Code Coverage, Code Review, Distributed Systems, Python (Programming Language), Systems Development Life Cycle, Data Streaming, Systems Architecture, Reliability of Systems, Backend, Containerization, Kubernetes, Apache Kafka, Api Design, Grpc, Data Pipelines, Data Generation
- **Published:** October 1, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/software-engineer-macro-quant-analytics-technology/49686959

## About the Role

operational best practices.Participate in code reviews and technical discussions to improve design, performance, and maintainability.What's required3-10 years of experience developing production-quality backend software in C#, with a strong focus on distributed systems and APIs (REST/gRPC).Proven experience designing, deploying, and supporting backend services or platforms in cloud or hybrid environments .Strong understanding of distributed system design, including data modeling, consistency, and time-series or event-driven architectures.Hands-on experience with streaming and messaging systems, such as Kafka, and building scalable data pipelines with derived data generation and persistence.Familiarity with containerized environments, such as Kubernetes, and modern data and storage technologies.Solid grasp of SDLC best practices, including testing, code coverage, monitoring, and operational support in production systems.Experience with Python and exposure to C++, particularly in

## Description

business.What you'll doDesign, build, and extend core C# analytics services, APIs, and libraries used across the Macro business.Develop and operate high-performance distributed systems with strong guarantees around correctness, latency, and scalability.Build real-time and historical analytics services supporting pricing, risk, and global market data workflows.Design and maintain time-aware (historical and real-time) data models and services, ensuring consistency across analytics use cases.Develop and integrate derived data pipelines and datasets used in research, backtesting, and production analytics.Contribute to API design, data modeling, and system architecture for shared analytics platforms.Integrate analytics services with batch and streaming data pipelines across research and trading workflows.Partner closely with quants and portfolio managers to translate investment requirements into robust platform capabilities.Contribute to system reliability through testing, monitoring, and