Lead Software Engineer - Data and Business Observability Platform

Jersey City, NJ, United States

• Job Identification
• Job Category Software Engineering
• Business Unit Commercial & Investment Bank
• Posting Date 10/06/2026, 08:08 PM
• Locations 545 Washington Blvd, Jersey City, NJ, 07310, US
• Job Schedule Full time
• Job Shift Day
• Base Pay/Salary Jersey City,NJ $-$

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer
- Data and Payments Business Observability Platform at JPMorgan Chase within the Commercial and Investment Banking
- Data Analytics Payment Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities

• Lead the design and delivery of an activity monitoring solution spanning a React UI and Java/Spring Boot backend services, ensuring scalability, resiliency, and a low-latency user experience with responsive APIs.
• Lead the design and evolution of event-driven microservices workflows, using Kafka for inter-service communication and reliable asynchronous processing (at-least-once delivery, retries, and DLQ patterns).
• Set and uphold engineering standards for the team’s Spring Boot services (API design, error handling, security, logging, performance tuning, versioning).
• Partner with product owners and stakeholders to translate monitoring/operational requirements into clear technical designs, delivery plans, and measurable outcomes.
• Design and maintain data access patterns across MySQL and Databricks, including connectivity, data retrieval strategies, and performance-efficient query patterns.
• Establish and evolve the deployment strategy (blue/green, canary, rollback, configuration management) aligned to engineering and operational needs on AWS.
• Own and improve CI/CD pipelines using Jenkins, including automated builds, tests, quality gates, release orchestration, and environment promotions.
• Design, build, and maintain the React-based UI, including performant, data-heavy grid experiences using AG Grid, state management, and frontend quality controls.
• Ensure production readiness through observability (metrics, logs, tracing), alerting, incident response runbooks, and proactive problem management.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns.
• Apply knowledge of SDLC tool chains, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Formal training or certification on software engineering concepts and 5+ years applied experience

• In addition, 2+ years in a technical lead / lead engineer role driving design and delivery with cross-functional partners and being an highly collaborative team player with strong ownership/accountability and a high-energy delivery mindset (bias for action, urgency, excellence)
• Strong hands-on expertise in Java and Spring Boot and strong working proficiency in Python for automation, data access utilities, and developer productivity tooling
• Proven experience designing and operating Kafka-based systems (topics/partitions, consumer groups, ordering, delivery semantics, retries/DLQs).
• Strong MySQL experience (schema design, indexing, query optimization, transactions) and solid data modeling skills
• Familiarity with No
  
  SQL data stores and search technologies (e.g., Elasticsearch) and when to use them
• Working experience with Databricks and practical knowledge of connecting applications to Databricks to retrieve data securely and efficiently.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity…