Software Engineer | Post Trade Analytics
- Salary
- ₹15–26 LPA
- Location
- Hong Kong
- Experience
- Intermediate
About the company & role
Jump Trading Group is committed to world-class research. We empower exceptional talent in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting-edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by fostering collaboration and mutual respect. At Jump, research outcomes drive more than superior risk-adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve complex problems. Jump Trading's Post-Trade Analytics (PTA) Team is the firm's central source of truth for understanding how we trade. We measure, analyze, and optimize every dimension of our trading activity across all global markets. Our team builds the foundational analyses that traders and quantitative researchers rely on daily to make critical decisions. Operating across highly diverse datasets, our core infrastructure collects, organizes, and stores billions of data points every day, powering the analytics behind a wide array of trading strategies. As a Data Engineer on the PTA team, you will own the critical datasets and pipelines upon which our trading decisions are built, all while developing in-depth technical and financial business expertise. What You'll Do: Partner directly with traders and quantitative researchers to turn complex questions into data products that shape how we trade across global markets. Build, operate, and scale the robust datasets and pipelines that power our post-trade analytics and research. Directly influence business priorities, trading strategies, and execution quality through high-impact data engineering. Guarantee trust in the numbers by building robust data validation frameworks, monito