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Senior Software Engineer (Real-Time)

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Onsite

Senior Software Engineer (Real-Time)

London Stock Exchange

Senior Software Engineer (Real-Time)

Skills

RustGolangKubernetesWorkday

1 month ago

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Important information


Contract type:

Permanent

Location:

London, UK

Work mode:

Onsite

Published on:

19 September 2026

What they need


  • As a Software Engineer in LSEG’s Real-Time Engineering organisation, you will work on a global low-latency market data platform that sends billions of price updates per-day around the globe
  • In this role, you will build APIs, telemetry pipelines and synthetic monitoring services that show how reliably and quickly market data reaches customers
  • You will work with experienced engineers to develop production software, measure performance and enable observability of a globally distributed platform
  • Prior market-data or observability experience is not required; we are looking for strong engineering fundamentals, curiosity and a willingness to learn
  • You will work with experienced engineers to build the software and data stack that measures how our Real-Time application delivers data from hundreds of global exchanges to thousands of customers
  • You will help turn software signals and synthetic monitoring data into useful end-to-end insight across LSEG’s Real-Time platform
  • You will contribute to software that brings together telemetry from individual applications and services, helping engineering and operations teams understand service health, performance and customer impact
  • This is a hands-on development role for an engineer at an early stage of their career who wants to build experience in mission-critical distributed systems, observability, cloud-native engineering and real-time financial technology
  • Build and improve software components that aggregate, correlate and present data from over 30 global distribution sites
  • Develop applications and data-processing logic that help identify performance issues, service degradation and hotspots across distributed systems
  • Contribute to telemetry pipelines that ingest, transform and route metrics, logs and traces into a common observability layer
  • Deliver synthetic monitoring capabilities that measure the performance and experience of Real-Time services from locations around the world
  • Develop APIs, automation and configuration used to manage observability services and capabilities
  • Use Git, CI/CD and configuration-as-code practices to deploy and maintain software and observability assets consistently across environments
  • Work with engineering squads to add and improve instrumentation within applications across Development, Test, PPE and Production environments
  • Work alongside expert engineers to learn modern approaches to observability, distributed systems, cloud-native software and real-time data platforms
  • Contribute ideas and improvements as the Real-Time observability platform continues to evolve- A good understanding of core software engineering concepts and an interest in building reliable, maintainable applications
  • Familiarity with APIs, Git and modern software development practices
  • A willingness to learn unfamiliar technologies and develop knowledge of complex systems
  • An interest in one or more of the following areas: market data, observability, distributed systems, telemetry, data pipelines, real-time systems, performance engineering or cloud-native technology
  • Hands-on software engineering experience, gained through employment, a graduate role, or open-source contribution
  • Ability to write and explain software in a performance-oriented languages such as Go, modern C++ or Rust
  • Demonstrated analytical and problem-solving ability in complex engineering or academic domain
  • Good communication and collaboration skills, with the ability to work effectively with engineers across different teams
  • Metrics, logging, distributed tracing or observability platforms
  • Financial markets, market data or other real-time or latency-sensitive systems
  • OpenTelemetry SDKs, collectors or telemetry standards
  • Kubernetes, containers or cloud platforms
  • CI/CD, GitOps or configuration-as-code approaches
  • Data-processing, event-streaming or telemetry-pipeline technologies
  • Synthetic monitoring, automated testing, probes or distributed agents

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