Software Engineer – Distributed Market Data Systems

Benefits

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

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About this role

Software Engineer – Distributed Market Data Systems London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Tick Data Platform is a new team building a globally distributed market data architecture. The systems are being developed from the ground up and we're looking for exceptional software engineers to join us in creating scalable and performant data platforms to support quantitative research and trading. Your future role within QRT - Greenfield development in a small and highly collaborative team - Building cloud-native platforms for the distribution and processing of realtime tick data - Architecting high throughput distributed systems with significant horizontal scalability - Working with researchers and data scientists across QRT Your present skillset: - 4 years of software engineering experience - Experience with distributed realtime systems - Systems design and architecture - Ability to write optimised and high throughput code - Communication and teamwork, with an interest in building a strong engineering culture Experience in these is advantageous but not required: - Cloud-native platforms including Kubernetes - Realtime platforms including Kafka - High performance python tooling (numpy, numba, c++ and rust interoperability) - Modern data tooling

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