Sr Lead Software Engineer - KDB+ / Q
JP Morgan Chase
Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank. You will be a core technical contributor in the Data Analytics team, building and refining KDB-based systems for real-time and historical market data. You’ll help migrate to AWS, re-architect applications, and drive greenfield projects with secure, scalable solutions. You will lead communities of practice and collaborate with stakeholders to deliver trusted, market-leading technology that aligns with the firm’s objectives. This role offers the opportunity to shape high-impact data platforms in a large, global institution.
Responsibilities- Execute creative software solutions and troubleshoot complex problems beyond routine approaches
- Develop secure, production-grade code and review others’ code
- Identify opportunities to automate recurring issues to improve stability
- Lead communities of practice to promote new technologies
- Foster team culture of diversity, equity, inclusion, and respect
- Develop core systems and frameworks based on KDB
- Lead team members via book of work management and drive SDLC improvements
- Develop scalable real-time processing solutions using agile methodology
- Partner with stakeholders to capture requirements and deliver solutions
- Collaborate with application support teams to maintain and support the platform
- Formal training or certification on software engineering concepts
- Hands-on experience in system design, development, testing, and operational stability
- Proficiency in automation and continuous delivery methods
- Strong understanding of Software Development Life Cycle and agile methodologies (CI/CD, application resiliency, security)
- Development lead experience: requirements capture, task decomposition, estimation, delivery planning, testing, UAT
- Deep understanding of KDB and Q language; at least 7 years professional KDB experience; plus 2+ years in a lead role
- Experience with KDB+tick design and data organization; performance implications of approaches
- Experience handling large datasets, optimizing query performance, scaling and load-balancing KDB apps, and building resilient/HA KDB systems
- Cross-functional collaboration
- Stakeholder partnership
- Mentorship and leadership
- KDB
- Q language
- AWS
Reference: WJ-747_30161790