Engineer, Commodities Quantitative Development

Overview

In this role, you will build and maintain quantitative tools and analytics to support commodities trading, working closely with multiple trading desks. You will translate traders’ needs into scalable software and data pipelines, enabling production-grade models for energy and commodities. You’ll join a cross-functional team at the intersection of quantitative modelling and software engineering, driving automation and reliable infrastructure. This is a hands-on, impact-focused position that blends research with engineering to empower Portfolio Managers and researchers.

Responsibilities

• Build, enhance, and maintain custom tools, models, analytics, and reusable software libraries used by trading teams
• Support and extend quantitative modelling frameworks, including power/energy dispatch models and related pipelines
• Develop and maintain data pipelines, interfaces, and integrations with internal and external trading, market-data, and analytics systems
• Partner with Portfolio Managers, traders, and researchers across desks to understand requirements and deliver practical solutions
• Perform day-to-day operational support and monitoring for proprietary trading systems; investigate and resolve issues promptly
• Collaborate with cross-functional technology and platform teams to deliver reliable, scalable infrastructure
• Identify manual or inefficient workflows and drive automation and process improvement
• Develop and maintain clear technical documentation, including system architecture, processes, and runbooks
• Work independently with sound engineering judgement, strong ownership, and minimal supervision

Key requirements

• 4+ years of hands-on software development experience, ideally supporting Portfolio Managers, traders, or investment teams
• Strong Python development skills, including experience with scientific and data libraries such as pandas, NumPy, SciPy, and related tooling
• Experience designing and maintaining production-grade software, including reusable libraries, APIs, data-processing workflows, and automated testing
• Experience building data-intensive applications or working with large-scale computational graphs, analytics platforms, or trading systems
• Experience with Snowflake, SQL, data pipelines, or analytics workflows
• Familiarity with AI tooling, including integrating LLMs, agentic workflows, retrieval systems, or other machine-learning-enabled applications into business processes
• An interest in or understanding of financial modelling or derivatives pricing
• Strong command of modern software-development practices: version control, code review, testing, CI/CD, and production monitoring
• Strong analytical and troubleshooting skills — able to assess complex problems logically and develop pragmatic solutions
• Excellent communication and documentation skills; able to explain technical concepts clearly to both technical and non-technical stakeholders
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience

• strong communication
• problem-solving mindset
• ownership and accountability
• Python with pandas/NumPy/SciPy
• production-grade software design
• data pipelines and analytics workflows

…