Jobs at Qube Research & Technologies

Evaluate and onboard macro financial datasets for quantitative research and trading. Assess data coverage, quality, consistency, APIs, and delivery mechanisms; develop Python tools and pipelines to extract, clean, normalize, and analyze data; investigate discrepancies across providers; improve dataset quality; and collaborate with researchers, traders, vendors, and engineering teams to automate reliable data integration.

Designs, implements, governs, and modernizes enterprise PKI services, including CA hierarchies, HSM integration, certificate lifecycle automation, machine identity management, trust models, disaster recovery, and operational controls. Serves as the primary PKI subject matter expert, advising engineering, cloud, security, risk, audit, and operational teams while leading PKI programs and transformations.

Develop and maintain C#/.NET applications and infrastructure for real-time data delivery across trading, risk, compliance, and operations. Build scalable data flows, optimize architecture and memory usage, investigate production performance issues, and improve system reliability. Contribute to React and TypeScript user interfaces while collaborating with technical and business stakeholders on trading and operational workflows.

Design, build, and operate distributed software and data platforms supporting quantitative research across cloud and on-premises environments. The role focuses on reliable, efficient data access for large-scale compute workloads, data movement, performance, security, observability, and resilience. Responsibilities include developing services and tooling, collaborating with researchers and engineers, and owning systems from design through production operations.

Architect, engineer, and oversee delivery of complex corporate, colocation, and ultra-low-latency trading networks. Responsibilities include lifecycle management of switching, firewalls, load balancers, telemetry, CMDB, and automation platforms; designing software-driven network solutions; managing WAN traffic prioritization and steering; collaborating with project teams and vendors; and maintaining expertise in emerging networking technologies.

Develop quantitative foundations for a risk and PnL management platform supporting trading across asset classes. Build risk models, scenarios, performance attribution, pricing integrations, and scalable analytics infrastructure. Collaborate with traders, quantitative researchers, pricing quants, and technology teams to translate requirements into production systems for real-time risk and performance management.

Lead Linux platform engineering for high-performance trading and research infrastructure. Responsibilities include workload scheduling, large-scale systems management, high-performance filesystem operations, software lifecycle management, kernel and network performance tuning, troubleshooting complex system issues, infrastructure automation, CI/CD, observability, and container orchestration. The role partners closely with research and infrastructure teams and provides technical leadership, strategic insights, and proof-of-concept evaluations.

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.

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.

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.