Software Engineer - Python/Java

Our client is a global trading firm that thrives on advanced research, sophisticated technology, and collaborative innovation. For over three decades, they’ve played a key role in maintaining stability within financial markets by offering vital liquidity. Their offices span the U.S., Europe, Asia-Pacific, and India, where quantitative researchers, engineers, traders, and operational teams work together in a high-performance environment rooted in shared success and social impact.

Whether exploring new asset classes, leveraging emerging technologies, or evolving research and trading approaches, our client embraces bold thinking and close collaboration to stay ahead.

They are currently seeking a highly motivated Software Engineer to join their Chicago team. In this role, you’ll work at the intersection of trading and technology — building the infrastructure, compute, and research tooling that powers large-scale analysis and market data processing for global trading strategies. You’ll collaborate directly with quant researchers and traders, delivering solutions that drive both performance and innovation.

Key Responsibilities:

• Design, build, and maintain scalable systems for compute, data access, and research tooling
• Develop infrastructure capable of handling large-scale jobs and complex storage challenges
• Collaborate with researchers and traders to understand workflows and rapidly prototype solutions
• Support a global team by contributing to tools and systems used across multiple regions
• Iterate quickly based on user feedback and usage patterns to enhance usability and performance
• Ensure seamless access to historical reference data and market data

Qualifications:

• 3+ years of software engineering experience with strong proficiency in Java and Python
• Hands-on experience managing Kubernetes clusters and containerized workloads
• Deep understanding of large-scale systems, big data infrastructure, and high-performance storage
• Strong interest in working alongside traders and researchers to improve day-to-day workflows
• Comfortable with rapid prototyping, fast iteration loops, and adjusting solutions in response to feedback