Jobs at Qube Research & Technologies

Develop and maintain compliance technology systems focused on market surveillance, regulatory reporting, data pipelines, automated controls, and integrations. Translate business and compliance requirements into production solutions, troubleshoot technical issues, implement surveillance scenarios, manage testing and releases, and improve automation, performance, and reliability. Collaborate with compliance, technology, developers, stakeholders, and external vendors while supporting systems across the trading and order execution lifecycle.

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.

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.

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.

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.

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.

Leads QRT’s global identity and access security capability, including IAM/IGA strategy, PAM, secrets management, authentication, authorization, access governance, and least-privilege programs. The role oversees Active Directory, cloud, application, infrastructure, production, and trading-environment access, while managing the IAM team, vendors, roadmaps, audits, incidents, and security improvements.

Build and maintain reliable financial datasets for quantitative researchers and traders. Responsibilities include extracting, cleaning, aggregating, and onboarding data from diverse sources; developing robust extraction processes; investigating data quality issues; and improving onboarding tools. The role requires close collaboration with researchers, traders, engineers, management, and external data providers in a fast-paced quantitative investment environment.

Develop and optimize high-frequency, low-latency cryptocurrency trading systems. Implement alpha and trading algorithms, encode market-specific rules, and collaborate with traders and quantitative researchers to build efficient research platforms and tools. The role requires robust C++ development on Linux, cloud-based HPC familiarity, Python skills, technical problem-solving, and effective communication in an international environment.

Provides deep technical leadership for QRT’s global trading and enterprise networks. Leads complex investigations involving performance, latency, resilience, and operations; serves as a senior escalation point; translates architecture standards into automation, validation, documentation, and runbooks; supports migrations and technical improvements; evaluates technologies; develops instrumentation; and mentors network engineers.

Leads QRT’s trading and enterprise network function through Network Team Leads. Owns network strategy, people development, priorities, project delivery, operations, risk management, architecture standards, stakeholder communication, and continuous improvement across multiple teams and sites. Ensures scalable, consistent, supportable network services aligned with business needs, while serving as the senior escalation point for operational, delivery, and people-related issues.

Design and develop scalable reference-data services, automate lifecycle events, build/internal and external reporting (real-time and batch), collaborate with research and execution teams, maintain CI/CD and automated testing, and integrate Python and C# components to support trading and research workflows.

Manage and evolve Linux platforms for global trading, lead automation frameworks, ensure performance, and support build/release management.

Support day-to-day operations of on-prem compute infrastructure, handle diagnostics, troubleshoot Linux systems, and participate in maintenance activities for HPC and Kubernetes environments.

Manage and maintain QRT's network infrastructure and automations. Responsibilities include incident resolution, developing monitoring tools, and supporting network automation.

Develop and enhance high throughput, Linux-based services within a core pricing and risk platform. Collaborate with traders and quants, focusing on low latency and distributed systems in C++ and Python.

Design, implement, and optimize ultra-low-latency C++ systems for trading and market data. Profile and tune CPU, cache, and memory performance, collaborate with FPGA and hardware teams, and integrate network and kernel-level optimizations to minimize latency in live trading environments.

Design and implement AWS deployment strategies, drive CI/CD practices, maintain cloud application monitoring, enhance scalability, and support operational troubleshooting.

Join Qube Research & Technologies as a Network Engineer responsible for designing large-scale datacentre networks, ensuring high-performance connectivity, and collaborating with teams to enhance infrastructure and troubleshooting.