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Qube Research & Technologies

Software Engineer - Data Lifecycle

Reposted One Month Ago
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In-Office
Sydney, New South Wales, AUS
Senior level
In-Office
Sydney, New South Wales, AUS
Senior level
The role involves designing and building scalable systems for trade lifecycle management, maintaining data integrity, and collaborating on reporting pipelines, while also handling production support.
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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 with stakeholders to translate business needs into reliable technical solutions
  • Writing well-tested, maintainable code and contributing to CI/CD and deployment pipelines
  • Supporting production systems and continuously improving reliability, monitoring, and performance

What we’re looking for

  • 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.

What will set you apart

  • 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

Why join QRT?

  • Work on business-critical systems with direct impact on trading outcomes
  • Join a core engineering team with significant ownership and autonomy
  • Collaborate with traders, researchers, and engineers in a highly technical environment
  • Tackle complex data and systems challenges at scale

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