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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, monitoring, alerting, data lineage, and executing rapid incident response. Drive performance by optimizing data processing and workflows for speed, cost, and resilience, while diagnosing and resolving the most complex pipeline and production issues. Develop and optimize the tools, documentation, and foundational infrastructure that empower the broader research and trading teams. Other duties as needed Skills You’ll Need: 3+ years of experience as a Data Engineer or Software Engineer working extensively with large-scale data. Proficiency in Python or C++ (Strong skills in at least one, with a willingness to work across both). Proven expertise in building, operating, and scaling ETL/ELT pipelines, including orchestration, scheduling, and dependency management. Strong command of SQL and the broader data analytics ecosystem, including familiarity with libraries such as Pandas and NumPy. Sharp analytical and problem-solving abilities, paired with a strong curiosity to understand the financial business logic behind the data. Comfort and proficiency working within Linux environments. Reliable and predictable availability
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.