Lead Software Engineer, Kdb, Equity Derivatives Systematic Trading

JPMorgan Chase JPMorgan Chase · Banking · Singapore · Commercial & Investment Bank

Lead KDB Engineer for JPMorgan Chase's Equity Derivatives Systematic Trading business, responsible for building and enhancing the KDB platform to support data analytics for trading strategies. The role involves designing scalable data stores and APIs, collaborating with quantitative research and trading teams, and ensuring operational stability of KDB applications.

What you'd actually do

  1. Design, develop, and deliver scalable KDB-based systems, capturing real-time and historical datasets for market data, risk & pricing and client analytics
  2. Collaborate with Electronic Trading and QR teams to capture requirements, implement data enrichment / analytics for implementing derivatives-based trading strategies and performance analysis.
  3. Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches.
  4. Act as Subject Matter expert for suite of KDB applications empowering Derivatives Systematic Trading
  5. Develop secure, high-quality production code; review and debug code written by others.

Skills

Required

  • KDB/Q
  • KDB+ tick design
  • data organization
  • performance optimization
  • large datasets
  • query performance optimization
  • resilient, high-availability KDB applications
  • system design
  • application development
  • testing
  • operational stability
  • automation
  • continuous delivery methods
  • agile methodologies
  • CI/CD
  • application resiliency
  • security
  • scaling KDB applications
  • load-balancing KDB applications

Nice to have

  • Terraform
  • Kubernetes
  • public cloud environments (AWS, Azure, GCP)
  • LLMs in search and/or analytics driven user workflows
  • prompt engineering
  • context engineering
  • Python
  • C
  • C++
  • Java

What the JD emphasized

  • formal training or certicfication on software engineering concepts
  • at least 5+ years of hands-on professional experience with KDB/Q
  • Deep understanding of KDB+ tick design, data organization, and performance optimization.
  • Experience developing and running large datasets, optimizing query performance, and building resilient, high-availability KDB applications.
  • Experience collaborating with quant, algo, or trading teams to deliver data solutions.