Jobs at Qube Research & Technologies

Designs and maintains financial market, pricing, and reference datasets for quantitative researchers and traders. Responsibilities include developing Python-based extraction and data processing workflows, building automated production pipelines, validating and troubleshooting data quality, onboarding new data sources, and managing evolving production data requirements. The role requires strong financial markets knowledge, advanced Python and data engineering skills, and collaboration with trading and quantitative research stakeholders.

Build and support a full-stack energy trading platform covering physical commodities, derivatives, nominations, positions, and risk. Collaborate directly with traders and business users to translate requirements into production features, extend support for new markets and products, maintain the platform, and contribute to technical direction and code quality.

Designs, builds, and maintains infrastructure supporting quantitative research and trading platforms. Responsibilities include developing CI/CD pipelines, managing AWS and EKS infrastructure, maintaining Docker and Kubernetes environments, automating on-premises production systems, implementing monitoring and security practices, and improving deployment reliability across globally distributed teams.

Build and enhance quantitative trading framework software, design clean architectures, and support reliable high-performance systems. Responsibilities include alerting, incident response, on-call participation, performance analysis, root-cause investigations, automation, self-healing capabilities, and defining service reliability metrics. The role partners with development teams to instrument applications and establish measurable SLIs, SLOs, and SLAs.

Develop pre-trade and post-trade analytics tools for automated trading strategies. Build trader dashboards, analyze market and trading data, and deliver analytics for execution quality, transaction costs, risk, positions, and strategy performance. Collaborate with traders and quantitative researchers while contributing to platform architecture, testing, monitoring, code reviews, and continuous process improvement.

As a DevOps Engineer, you will ensure the reliability, scalability, and performance of database platforms, automate operations, and support Kubernetes adoption, while collaborating with engineering and data teams.

Leads QRT’s academic partnerships and research engagement programs globally. Builds relationships with universities, academics, and research groups; shapes collaborative research projects, publications, conferences, visiting initiatives, and student programs. Identifies emerging research talent, scales partnership models across regions, aligns collaborations with QRT’s research and talent priorities, and coordinates with internal operations and research teams.

Provide first-line data support to quantitative researchers and traders, troubleshoot data access and quality issues with data engineers, manage JIRA workflows, document data processes, onboard and train users, and help expand data coverage through live collection and backfills.

Build, administer, automate, and evolve QRT’s global Linux and low-latency trading platforms. Serve as the APAC platform engineering representative, provide regional engineering coverage, align local infrastructure with global standards, and contribute to architecture, monitoring, performance tuning, incident support, and engineering projects. Partner with infrastructure and application teams to define tooling, configuration management, build and release processes, and scalable platform standards.

Designs and implements secure, scalable AWS architectures supporting quantitative research and large-scale data analysis. Collaborates with researchers, developers, and data scientists; automates infrastructure deployment and monitoring; optimizes performance, availability, reliability, and cost; troubleshoots complex cloud environments; and promotes AWS best practices across the specialist team.

Designs and implements secure, scalable AWS architectures supporting quantitative research, modeling, and large-scale data analysis. Collaborates with researchers, developers, and data scientists to deliver reliable cloud solutions. Automates infrastructure deployment, management, and monitoring; optimizes performance, availability, scalability, and cost efficiency; troubleshoots complex cloud environments; and promotes AWS best practices across the team.

Designs and implements secure, scalable AWS architectures supporting quantitative research and large-scale data analysis. Collaborates with researchers, developers, and data scientists to translate requirements into reliable cloud solutions. Automates infrastructure deployment, management, and monitoring; optimizes performance, availability, scalability, and cost efficiency; troubleshoots complex cloud environments; and promotes AWS best practices across the specialist team.

Provide first-line support to quantitative researchers and traders using extensive datasets. Resolve data access and quality issues with data engineers, manage JIRA support workflows, onboard and train new users, maintain documentation, and help extend data coverage through live collection and backfills.

Own the full lifecycle of cloud and on-premises infrastructure supporting trading and research workloads. Design AWS deployments, manage Docker and Kubernetes platforms, drive CI/CD and infrastructure-as-code adoption, and build reliable networking, security, monitoring, and automation solutions. Partner with engineers, researchers, trading desks, and business stakeholders to deliver scalable production infrastructure and define architecture in evolving environments.

Conduct quantitative and fundamental research on base metals, developing supply-demand balances, physical-market datasets, fair-value models, predictive signals, and trading strategies. Responsibilities include vessel tracking, end-use demand modeling, incentive and arbitrage analysis, backtesting, scenario analysis, and performance attribution. Automate research workflows using Python, SQL, and APIs while maintaining reproducible, version-controlled datasets and communicating findings to traders, technologists, and portfolio managers.

Translate business and regulatory requirements into reference data models, datasets, data quality rules, workflows, and documentation. Partner with architects and stakeholders across Trading, Compliance, Operations, and Research. Serve as a subject matter expert on equity and ETF reference data, corporate actions, identifiers, lifecycle processing, and downstream impacts. Support data interrogation using SQL and contribute to system delivery, data dictionaries, entity relationship diagrams, requirements specifications, and exception-management metrics.

Five- to six-month data engineering internship supporting quantitative research and trading platforms. The intern may work on data acquisition, large-scale datasets, data stores, APIs, production datasets, and real-time or batch data infrastructure. Responsibilities emphasize reliability, performance, scalability, and collaboration with researchers, traders, and engineers. Candidates should have computer science fundamentals, Python experience, structured problem-solving skills, and clear communication. SQL or NoSQL knowledge, front-end experience, and financial markets interest are preferred.

Infrastructure engineering internship or graduate role supporting research, trading, and business systems. Responsibilities may span hardware, Linux operating systems, high-performance computing, storage, networking, DevOps, platform engineering, or site reliability. Candidates contribute to automation, monitoring, incident response, performance optimization, and reliable scalable infrastructure across cloud and on-premise environments.

Contribute to production FPGA systems for ultra-low-latency trading. Design, optimize, test, verify, and integrate hardware and software components using SystemVerilog, C++, and Python. Analyze latency, resource utilization, and power efficiency while debugging designs and developing functionality for market-data processing and order execution. Collaborate with hardware and software engineers and support research into improved FPGA performance.

Design, develop, and support production-grade trading applications, APIs, distributed systems, web tools, deployment automation, and workflow platforms. Build scalable, observable, resilient software for traders, researchers, operations teams, and engineers. Collaborate with stakeholders, contribute to architecture, automate deployment and operational processes, and support systems across global production environments. The role emphasizes reliability, performance, maintainability, cloud technologies, and ownership throughout the software lifecycle.