Qube Research & Technologies

Software Engineer - Research Platforms

In short

Senior Software Engineer role on QRT's Data Engineering team, building and operating distributed software that gives Quantitative Researchers reliable access to data across cloud and on-premises environments. The company is a global quantitative and systematic investment manager with a technology- and data-driven culture. Requires 5+ years building production systems, strong skills in Go, Python, C++, Rust or Java, and experience designing distributed systems at scale. Fully remote full-time position.

About the Role
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. QRT is a technology- and data-driven group implementing a scientific approach to investing, combining data, research, technology, and trading expertise to solve complex challenges.
You will join the Data Engineering team, which builds software that enables Quantitative Researchers to access and use data across cloud and on-premises computing environments. The team works with other engineering groups to support data-intensive research workloads.
Responsibilities
•Design, build and operate distributed software that manages data across research environments.
•Enable reliable and efficient data access for large-scale compute workloads.
•Address challenges involving data movement, locality, performance and scale.
•Develop services and tooling used by Quantitative Researchers and engineering teams.
•Improve the security, observability and resilience of data systems.
•Work with researchers and engineers to understand requirements and deliver practical solutions.
•Own systems from design and implementation through production operation.
Requirements
•At least five years of experience building and operating production software systems.
•Strong software engineering skills in Go, Python, C++, Rust, Java or a similar language.
•Experience designing distributed systems at scale, with an understanding of performance, concurrency, fault tolerance and reliability.
•Experience building services or platforms used by other engineers.
•Knowledge of large-scale storage, data movement, or data-intensive computing workloads.
•Understanding of how storage and networking affect distributed system performance.
•Experience working across cloud and on-premises environments.

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