Lead Software Engineer - Reference Data Engineering

Join JPMorganChase’s Corporate Sector Reference Data Engineering group in Chicago, IL (onsite) to build and deliver trusted, secure, stable, scalable real-time reference data platforms. This role focuses on modern data mesh architecture and the creation of Java and Spring Boot microservices and data pipelines on AWS, Databricks, and on-prem, with streaming and evolving AI/ML-driven data quality capabilities.

You will lead end-to-end feature delivery, help elevate engineering standards, and drive adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes. The team also contributes to shared knowledge through documentation, runbooks, and technical talks.

Responsibilities

• Execute creative software solutions through design, development, and technical troubleshooting that goes beyond routine approaches
• Develop secure, high-quality production code, and review and debug code written by others
• Drive team adoption of enterprise-authorized AI-assisted engineering practices, including AI-assisted code review and refactoring, test strategy acceleration, and support for incident and root-cause analysis, while establishing consistent validation standards such as secure coding, peer review, and automated testing
• Apply tools across the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation, to increase the value delivered by automation
• Design and develop Java/Spring Boot microservices for real-time data product delivery and platform capabilities
• Own assigned features end-to-end: requirements, design, implementation, testing, deployment, and monitoring
• Optimize performance, scalability, and cost efficiency of microservices and data pipelines, backed by comprehensive unit, integration, and end-to-end tests to protect reliability and data integrity
• Participate in design and code reviews, proactively remediate technical debt, and support production and incident response
• Contribute to team knowledge sharing through documentation, runbooks, and tech talks

Requirements

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Ability to drive team adoption of enterprise-authorized AI-assisted engineering practices with consistent validation standards (secure coding, peer review, automated testing) and reuse of effective patterns
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Expert-level Java proficiency, including deep knowledge of Spring Boot, Spring Cloud, Spring Data, and Spring Security (JWT/OAuth2) and AWS experience building cloud-native or cloud-ready applications
• Strong understanding of distributed systems, microservices architecture, and design patterns
• Production-level experience with AWS services such as EC2, S3, Lambda, CloudWatch, IAM, and Kinesis, plus hands-on database experience including MongoDB, Snowflake, Databricks, and relational SQL
• Experience with version control (Git/Bitbucket), CI/CD pipelines, and modern DevOps practices (Docker, Kubernetes, Terraform) to support the full SDLC and continuous delivery
• Proficiency in Java/J2EE and REST APIs, including event-driven microservices and Kafka-related architectures using technologies such as Kinesis and Spark Structured Streaming, plus message brokers such as Kafka and RabbitMQ
• Hands-on experience with system design, application development, and testing with proficiency in Git/Bitbucket, JIRA, and Maven
• Ability to tackle design and functionality problems independently with clear articulation of technical concepts and high ownership of quality and delivery

Technologies

• Java, Spring Boot, Spring Cloud, Spring Data, Spring Security (JWT/OAuth2), Spring Framework, AWS
• EC2, S3, Lambda, CloudWatch, IAM, Kinesis
• MongoDB, Snowflake, Databricks, SQL
• Git, Bitbucket, CI/CD pipelines, Docker, Kubernetes, Terraform
• Java/J2EE, REST APIs, Kafka, RabbitMQ, Spark Structured Streaming
• JIRA, Maven

Preferred Qualifications, Capabilities, and Skills

• Python with data engineering experience, including exposure to Databricks, and a background in data infrastructure or reference data platforms
• Experience in Platform or Product Development and contribution to open-source projects or public technical content
• AWS Certifications (AWS Certified Solutions Architect - Associate or higher)
• Experience with Spring Cloud (Netflix OSS stack: Eureka, Zuul, Hystrix)
• Experience building or maintaining high-scale, real-time data systems, familiarity with data product delivery and data mesh patterns
• Experience with multi-region or disaster recovery scenarios
• Familiarity with managed service architecture patterns

About the Team

JPMorganChase Corporate Functions professionals cover a range of areas from finance and risk to human resources and marketing. Corporate teams play an essential role in supporting businesses, clients, customers, and employees for success.

Compensation: USD 137,750 - 185,000 per year.