G-Re

Network Automation Engineer (Contract)

G-Re
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23 hours ago
London, United KingdomMid Level

Responsibilities

  • Design and develop core components of a distributed storage platform in Rust.
  • Build scalable, resilient, and performant systems for large data workloads.
  • Collaborate with researchers and engineers to understand data-access requirements.
  • Contribute to architectural decisions across distributed systems and data management.
  • Develop and optimize services running in Kubernetes environments.
  • Integrate event-driven and streaming technologies, including Kafka, into the platform.
  • Promote engineering best practices, code quality, thorough testing, and operational excellence.

Requirements

  • Commercial experience developing production systems in Rust.
  • Solid grounding in distributed systems and the trade-offs involved in designing them.
  • Experience building systems that reliably handle large volumes of data.
  • Kubernetes experience is beneficial.
  • Familiarity with event-driven or streaming technologies such as Kafka is desirable.
  • Ability to collaborate and clearly explain technical decisions to colleagues.
  • Commitment to testing, code quality, and operational excellence.

Benefits

  • Highly competitive compensation.
  • Lunch provided via Just Eat for Business and a dedicated barista bar.
  • Informal dress code and excellent work/life balance.
  • Monthly company events.
  • London-based contract applications are handled through a third-party recruitment partner.
G-Re

About G-Re

1,001-5,000 employees

G-Research is a London-based quantitative research and technology firm that develops models, data pipelines, and trading systems to forecast movements in global financial markets. It employs researchers and software engineers to build machine-learning-driven strategies and the infrastructure that supports systematic investing, spanning high-performance compute and secure networks. Privately held and founded in 2001, the company operates from its London headquarters and focuses on institutional, data-intensive finance.

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