Jobs at Qube Research & Technologies

Develop and maintain production tools supporting voice and electronic trading execution across asset classes. Build dashboards and visualization tools, deliver features through rapid user feedback, own production stability and reliability, and evolve the technology stack to meet changing market requirements. Collaborate closely with front-office business users in a fast-paced quantitative investment environment.

Supports market data change across business and technology teams by gathering requirements, defining functional specifications and acceptance criteria, analyzing system and workflow impacts, mapping data flows and dependencies, coordinating stakeholders, supporting testing and validation, and managing actions and timelines through implementation.

Develop high-performance C++ applications for ETF market making and electronic trading. Build pricing, quoting, execution, and market data components; implement quantitative models; optimize latency, throughput, and resilience; and collaborate with quantitative researchers, traders, and engineers to support live trading systems.

Develop and maintain high-performance, reliable software systems and reusable infrastructure components. Solve complex challenges involving concurrency, memory management, system performance, and reliability. Own technical designs, contribute to architecture, investigate production issues, improve system robustness, collaborate with quantitative researchers and engineers, and support code reviews, testing, and engineering best practices.

Build and scale cloud observability platforms across AWS and EKS/Kubernetes. Develop telemetry collection, storage, routing, alerting, onboarding automation, service ownership integration, and PagerDuty workflows. Establish reusable standards for logs, metrics, dashboards, scrape targets, and alert rules while reducing operational toil. Partner with cloud, platform, observability, and service teams to drive adoption and ensure the platform remains reliable, scalable, and independently operable.

Operate and improve global hybrid cloud and network infrastructure across AWS, on-premises, WAN, internet, and datacenter environments. Lead incident response, root-cause analysis, observability, automation, infrastructure-as-code governance, reliability roadmaps, backlog delivery, and vendor coordination. Build monitoring, self-healing automation, runbooks, and controlled Terraform-based network changes while supporting 24/7 operations, on-call escalation, maintenance windows, and major incident response.

Leads a regional Network Operations team supporting critical global infrastructure. Responsibilities include team management, incident coordination, vendor escalation, rota and out-of-hours support, operational readiness, monitoring, automation, service-level reporting, documentation, and continuous improvement. The role coordinates across global infrastructure, engineering, security, trading, vendors, and connectivity providers while acting as the regional escalation point for network incidents and service risks.

Design and build high-performance, reliable software systems and reusable components. Own technical designs, contribute to architecture, solve concurrency and performance challenges, troubleshoot complex issues, and improve system robustness. Develop production-grade software in Linux environments, participate in code reviews and automated testing, and collaborate with researchers and engineering teams to deliver effective technical solutions.

Build and scale global data lakehouse solutions supporting quantitative trading desks. Develop Python and SQL data pipelines in AWS, model large-scale lake and OLAP data, optimize cross-region performance, ensure data quality and completeness, and deliver tailored data solutions for quants and traders.

Leads the regional Network Operations team across EMEA and America, managing engineers, rotas, escalations, vendors, incidents, maintenance, and operational readiness. Oversees network service reliability, monitoring, alert quality, automation, SLIs, SLOs, KPIs, documentation, and continuous improvement. Coordinates major incidents and global follow-the-sun support while partnering with Infrastructure, Engineering, Trading, Security, and external connectivity providers. The role includes people management, hiring, coaching, on-call participation, out-of-hours escalation, and maintenance-window support.

Build and operate high-performance software for options trading, including low-latency execution engines, research tools, and analytics infrastructure. Collaborate closely with quantitative researchers and traders to deliver robust systems from concept through production. Apply modern C++ and Python alongside strong computer science fundamentals and knowledge of CPU architecture, memory, operating systems, and networking in a fast-paced trading environment.

Leads the global market data platform engineering team, managing people, reliability, data quality, scalability, infrastructure, delivery, troubleshooting, testing, observability, automation, and stakeholder coordination across trading, exchange, vendor, and technology environments.

Internship opportunities focused on HR data analytics and HR software engineering. Responsibilities include building AWS data pipelines, HR system integrations, full-stack applications, BI dashboards, automation services, APIs, monitoring, documentation, and secure data workflows. Interns collaborate with HR, analytics, engineering, and business stakeholders while applying Python, Kotlin, SQL, cloud technologies, and modern web frameworks. The program is designed for penultimate- or final-year bachelor's or master's students and may lead to a graduate role.

Build and deploy cloud-native full-stack HR technology tools, secure APIs, middleware, data pipelines, and automated workflows. Develop React or Python Dash interfaces, Python and Kotlin services, and AWS integrations using S3, ECS, and Lambda. Implement testing, logging, monitoring, and error handling while translating HR needs into technical solutions. Ensure documentation, GDPR compliance, data privacy, and financial-services security standards when improving employee lifecycle processes.

Interns will analyze financial, market, portfolio, and business data; develop prototypes, dashboards, visualizations, and analytical tools; support investment research; and evaluate AI agents and data applications. Tracks include Applied AI Engineering, Applied Data Science, and Investment Analytics. The role requires Python, data modeling, statistical analysis, clear communication, and the ability to solve open-ended problems in collaboration with developers and business stakeholders.

Surveillance Interns monitor global trading activity, review alerts, investigate potentially suspicious behavior, analyze order and trade data, and support market-abuse detection. They will help test surveillance thresholds, integrate markets and data sources, improve monitoring tools, build automation and data-quality controls, and collaborate with Compliance, Trading, Risk, and Technology teams.

Build and maintain scalable, high-performance systems for trade and position lifecycle management, reference data, reporting, and front-office analytics. Automate financial lifecycle events, ensure data quality and system robustness, develop tested code, support CI/CD and production systems, and collaborate with trading, research, risk, operations, brokers, and fund administrators.

Provides technical leadership for a global quantitative development team. Builds and supports quantitative research tools, automates large-scale data preparation and cleansing, improves software engineering practices, and helps researchers productionize trading strategies. The role requires strong Python development, maintainable software design, testing, collaboration, and adoption of agentic coding workflows in a fast-paced investment environment.

Develop Python applications, quantitative tools, data pipelines, and cloud infrastructure supporting commodity trading and research across agriculture, metals, and energy. Build pricing, backtesting, risk, PnL, statistical modeling, and machine learning solutions; integrate alternative datasets; automate workflows; and maintain reliable research and trading systems while collaborating with researchers, traders, data engineers, and infrastructure specialists.

Build and operate AWS-based data pipelines, datasets, and analytics applications for business stakeholders. Integrate and validate internal and external data, develop BI views, maintain infrastructure through code and CI/CD, and contribute to LLM-powered projects. The role also involves documenting systems, using agentic coding tools, and translating ambiguous business questions into reliable data products and insights.