Qube Research & Technologies
quantitative and systematic investment manager
SoftwareEngineer-DataLifecycle
Neural analysis suggests this role is
optimal for Mid candidates.
“Software Engineer - Data Lifecycle at Qube Research & Technologies. Skills: Data Lifecycle Engineering, Core Systems Development, Scalable Systems Design, High-Performance Systems. Designing and building scalable, high-performance systems for trade and position lifecycle management. Developing solutions to automate lifecycle events such as corporate actions, expiries, and cash flows across asset classes”
What You'll Achieve.
deliver high-quality returns for our investors; direct impact on trading outcomes
Industry & Context.
tackle complex problems; problem-solving skills with a focus on performance, scalability, and data quality; Tackle complex data and systems challenges at scale
What They're Looking For.
Must Have
5–10 years of software engineering experience, programming skills in Python, Solid understanding of software design, architecture, and scalable systems, Experience working with SQL and relational databases, Familiarity with testing frameworks and CI/CD practices
Nice to Have
experience with C#, exposure to financial markets, 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, interest in learning and working in a trading environment, Experience building systems in a quantitative trading or financial environment
What You'll Do.
Designing and building scalable
high-performance systems for trade and position lifecycle management
Developing solutions to automate lifecycle events such as corporate actions
and cash flows across asset classes
Building and maintaining high-quality reference data platforms used across trading and research
Delivering real-time and end-of-day reporting pipelines for internal and external stakeholders
Ensuring data accuracy
and consistency across systems and workflows
Contributing to system validation
and operational robustness
including alignment with brokers and fund administrators
Supporting production systems and continuously improving reliability
How You'll Work.
Team & Collaboration
work closely with trading, research, risk, and operations teams; Collaborating closely with stakeholders to translate business needs into reliable technical solutions; Collaborate with traders, researchers, and engineers
Communication Scope
Clear communication skills
Full Job Description
Software Engineer – Core - Data & Lifecycle Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating across all liquid asset classes worldwide. We are a technology and data-driven organisation applying a scientific approach to investing. By combining data, research, technology, and trading expertise, we tackle complex problems in a highly collaborative environment. Our culture of innovation underpins our ambition to deliver high-quality returns for our investors. Your role at QRT We are looking for a Software Engineer to join our Core Data & Lifecycle Engineering team in Sydney. This team builds and owns critical systems that sit at the heart of QRT’s trading operations—powering trade and position lifecycle management, reference data, and reporting workflows across all asset classes. These systems are highly visible and directly influence trading decisions, risk management, and operational efficiency. This is primarily a hands-on engineering role (≈80% development), with a smaller component (≈20% support and system ownership) focused on maintaining robustness, reliability, and data quality in production. You’ll work closely with trading, research, risk, and operations teams, gaining strong exposure to the business while building scalable, high-performance systems. What you’ll work on Designing and building scalable, high-performance systems for trade and position lifecycle management Developing solutions to automate lifecycle events such as corporate actions, expiries, and cash flows across asset classes Building and maintaining high-quality reference data platforms used across trading and research Delivering real-time and end-of-day reporting pipelines for internal and external stakeholders Ensuring data accuracy, integrity, and consistency across systems and workflows Contributing to system validation, controls, and operational robustness, including alignment with brokers and fund administrators Collaborating closely
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