As a Lead Software Engineer at JPMorganChase within the Corporate Sector's Reference Data Engineering, 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. This group powers one of the teams' most critical data-driven capabilities through a modern data mesh architecture delivering curated, domain-driven data products in real-time across the firm. Operating at enterprise scale across AWS, Databricks, and on-premises, Reference Data Integration (RDI) manages multi-tenant data delivery with managed-service enablement. The platform uses event-driven streaming (Kafka, Kinesis, Spark Structured Streaming) for high-performance real-time data delivery and is evolving AI/ML-driven data quality and reconciliation capabilities. Join our engineering team to architect intelligent, self-healing data platforms driving the next generation of financial infrastructure
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Executes creative software solutions through innovative system design and development. Approaches complex data infrastructure challenges with ability to think beyond conventional approaches
Develops secure, high-quality production code. Reviews and debugs code written by others. Maintains and elevates engineering standards
Designs and develops Java/Spring Boot microservices for real-time data product delivery and platform capabilities
Owns assigned features end-to-end: requirements, design, implementation, testing, deployment, and monitoring
Optimizes performance, scalability, and cost efficiency of microservices and data pipelines while writing comprehensive tests (unit, integration, end-to-end) to ensure platform reliability and data integrity
Participates in design and code reviews. Proactively identifies and remediates technical debt and helps with production support and incident response.
Contributes to team knowledge sharing: documentation, runbooks, tech talks
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Expert-level Java proficiency. Deep knowledge of Spring Boot, Spring Cloud, Spring Data, and Spring Security (JWT/OAuth2), Spring Framework, Spring Boot, and AWS Services in public cloud infrastructure, with experience building cloud-native or cloud-ready applications using AWS
- Strong understanding of distributed systems, microservices architecture, and design patterns
- Production-level experience with AWS: EC2, S3, Lambda, CloudWatch, IAM, Kinesis. Hands-on with databases: NoSQL (MongoDB), columnar/analytics (Snowflake, Databricks), relational SQL
- Experience with version control (Git/Bitbucket), CI/CD pipelines, and modern DevOps practices (Docker, Kubernetes, Terraform) so you can be proficient in all aspects of the Software Development Life Cycle (SDLC), agile methodologies, and continuous delivery
- Proficiency in Java/J2EE and REST APIs. Experience building event-driven Microservices and Kafka (Kinesis, Spark Structured Streaming) and its event-driven architecture and message brokers (Kafka, RabbitMQ)
- Hands-on experience with system design, application development, testing with proficiency in GIT/Bitbucket, JIRA, Maven
Ability to tackle design and functionality problems independently with little to no oversight. Clear articulation of technical concepts in a self-motivated role that requires high ownership of work quality and delivery
Python with data engineering experience including exposure to Databricks and a 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 in multi-region or disaster recovery scenarios
Familiarity with managed service architecture patterns
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
JPMorganChase Chicago, Illinois, USA Office
Chicago, IL, United States
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