Lead Software Engineer, KDB, Equity Derivatives Systematic Trading

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Lead KDB Engineer at JPMorgan Chase within Equities Trading you will play a pivotal role in building our next-generation KDB platform to support JPMorgan Chase’s Equity Derivatives Systematic Trading business. You will design and deliver scalable analytics stores and APIs that enable Quant teams to research for signals and implement trading strategies. In this role, you’ll work closely with Electronic Trading Tech, Quantitative Research, and trading teams. This is a unique opportunity to shape the core data infrastructure for our systematic trading platform as we modernize our technology stack.

Job Responsibilities

• Design, develop, and deliver scalable KDB-based systems, capturing real-time and historical datasets for market data, risk & pricing and client analytics
• Collaborate with Electronic Trading and QR teams to capture requirements, implement data enrichment / analytics for implementing derivatives-based trading strategies and performance analysis.
• Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches.
• Act as Subject Matter expert for suite of KDB applications empowering Derivatives Systematic Trading
• Develop secure, high-quality production code; review and debug code written by others.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability.
• Partner with application support teams to maintain and support the platform.

Required Qualifications, Capabilities, and Skills

• Bachelor's degree in Computer Science or equivalent
• Formal training or certicfication on software engineering concepts and 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.
• Hands-on experience with system design, application development, testing, and operational stability.
• Proficiency in automation and continuous delivery methods.
• Advanced understanding of agile methodologies such as CI/CD, application resiliency, and security.
• Experience with scaling and load-balancing KDB applications.

Preferred Qualifications, Capabilities, and Skills

• Experience with Terraform and Kubernetes for managing production environments in public cloud.
• Design and architecture of public cloud applications - AWS (preferable), Azure, GCP
• Use of LLMs in search and/or analytics driven user workflows, familiarity with prompt and context engineering
• Experience with other programming languages (e.g., Python, C, C++, Java).