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Join the infrastructure team at QRT to manage the physical build and operations of data centres and co-location facilities, ensuring high performance and security standards.

Deliver high quality analytics of trading data, develop reports, and support senior management with strategic insights. Collaborate with traders to manage risks.

The role involves creating predictive crypto trading signals, monitoring strategies, analyzing data sets, and collaborating with researchers.

The role involves designing and maintaining reliable systems, troubleshooting performance issues, collaborating with teams, and ensuring compliance and security standards.

The Lead Database Engineer will support, administrate, and secure databases, working closely with users to transform business needs into database solutions.

Develop, maintain, and support a research framework used by quantitative researchers. Build core components, tools, and APIs; troubleshoot deployments and runtime issues; manage releases, dependency management, CI/CD, and production monitoring; analyze performance and optimize production behavior. Work closely with researchers to translate feedback into framework improvements and provide day-to-day technical support.

As a Software Engineer at QRT, you will design and implement solutions for trade and position lifecycle automations, focusing on derivatives reference data and events while collaborating with various stakeholders.

Support, administrate, and secure databases while addressing information flow issues and transforming requirements into database solutions.

Own and evolve software platforms for the Volatility Risk team. Refactor and harden Python codebases, build backend services (pricing engines, market-data frameworks, risk analytics), create dashboards and UIs, and apply AI agents and automation to improve workflows. Partner with Risk Managers to industrialise processes and deliver production-grade, scalable solutions.

Support Options trading by sourcing, evaluating and onboarding datasets; build and maintain robust data pipelines; ensure data quality and timeliness; collaborate with researchers, traders and vendors to translate requirements into scalable data solutions and improve internal data platform and tooling.