Software Engineer - Data Lifecycle

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

You will join QRT’s Data team as a Software Engineer, working at the intersection of engineering, trading, and research. Your focus will be on delivering scalable systems for reference data management, regulatory and external reporting, and front-office analytics. This role offers direct visibility across the business and the opportunity to collaborate with stakeholders across Execution, Engineering, and Research teams. Every project you work on will contribute to operational efficiency and trading decision-making.

• 5–10 years of software engineering experience, ideally in a high-performance or data-intensive environment
• Strong programming skills in Python (experience with C# is a plus)
• Solid understanding of software design, architecture, and scalable systems
• Experience working with SQL and relational databases
• Familiarity with testing frameworks and CI/CD practices
• Domain experience (one or more is valuable, not required). We’re interested in engineers with exposure to financial markets, particularly:

- Trade and position lifecycle systems

- Equities, ETFs, futures, or options

- Corporate actions and reference data

• Market structure and exchange-specific behaviour
• Deep expertise in a single asset class is not required—but an interest in learning and working in a trading environment is important.

Nice to have 

• Experience building systems in a quantitative trading or financial environment
• Strong problem-solving skills with a focus on performance, scalability, and data quality
• Ability to operate in a high-impact, fast-paced environment with evolving requirements
• Clear communication skills and a collaborative mindset