Requirements

• 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
• Interest in learning and working in a trading environment

Nice to haves

• Domain experience in financial markets, including trade and position lifecycle systems, equities, ETFs, futures, options, corporate actions, reference data, or market structure
• Experience building systems in a quantitative trading or financial environment
• Strong problem-solving skills focused 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

What you'll be doing

• Designing and building scalable, high-performance systems for trade and position lifecycle management
• Developing automation solutions for lifecycle events such as corporate actions, expiries, and cash flows across asset classes
• Building and maintaining high-quality reference data platforms used by trading and research teams
• 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

Perks and benefits

• 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
• Initiatives and programs to support a healthy work-life balance
• Diverse and inclusive work environment that values respect and collective success