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Software Engineer | Post Trade Analytics

Hong Kong

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time - Experienced
From the employer’s posting
Apply at Jump Trading

What you’ll work on

Full posting
  • Partner with traders and quant researchers to turn their questions into data products

  • Build, operate and scale datasets and pipelines for post-trade analytics

  • Build data validation, monitoring, alerting and lineage; respond quickly to incidents

  • Optimize data processing and workflows for speed, cost and resilience

  • Diagnose and resolve complex pipeline and production issues

From the employer’s posting
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.
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
diagnosing and resolving the most complex pipeline and production issues

Tools in this posting

  • C++
  • Python
  • SQL
  • NumPy
  • pandas
Source — Tool mentions in context
- 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.
- 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.

Posting record

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Open 6 monthsWe first saw this posting 197 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Apr 15, 2026 · 197 days ago
Recorded sightings
220
Last seen by us
Oct 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the pay range before committing time to the process.

Complete your application on www.jumptrading.com. The employer’s form will show what is required.

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Job description

View original posting ↗

 

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
Source details

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Hong Kong

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