Lead Software Engineer - Java

JPMorgan Chase & Co.; Houston (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer within the Corporate Data and Analytics Services team to advance our data strategy and solutions, including the Corporate Data Catalog, Data Lineage, Entitlements, and Data Quality frameworks.

You will drive enterprise AI-assisted engineering practices, mentor engineers, and lead architectural evaluations with vendors to shape durable data platforms and scalable services.

Qualifications

• Formal training or certification on software engineering concepts plus 5+ years applied experience.
• Expertise building enterprise Java services – Java, Spring Boot, RESTful APIs and microservices at scale.
• Strong data engineering foundations – SQL/NoSQL (Oracle, MongoDB), Kafka, Elasticsearch or Gemfire.
• Databricks or Snowflake; modern data mesh/data product patterns.
• Ownership of test automation and CI/CD with accountability for resiliency and security.
• Proven technical leadership in Agile teams and mentoring engineers.
• Experience using AI-assisted development tools and validating AI outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows with secure data handling.

Responsibilities

• Executes creative software solutions, design, development, and troubleshooting.
• Develops secure, high-quality production code and reviews code written by others.
• Drives team adoption of enterprise AI-assisted engineering practices to improve code quality, speed, and outcomes.
• Applies SDLC tools including AI-assisted development to improve automation value.
• Identifies opportunities to automate remediation and improve operational stability of apps and systems.
• Leads evaluation sessions with external vendors and internal teams to assess architectural designs and applicability.

Skills

Java

Spring Boot

RESTful APIs

Microservices

Agile teams

AI-assisted software development

CI/CD

Secure coding

Code review

Tools

Docker

Kubernetes

Kafka

Elasticsearch

Gemfire

Jenkins

Spinnaker

JUnit

Mockito

Job description

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 at JPMorganChase within the Corporate Data and Analytics Services team, you'll play a crucial role in advancing our data strategy and solutions. As part of the Data Core Engineering group within CDAS, you'll contribute to executing the CT Data Strategy by developing key data solutions, including the Corporate Data Catalog, Data Lineage, Entitlements, and Data Quality frameworks.

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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Strong experience building enterprise Java services – Java, Spring Boot, RESTful APIs and microservices at scale.
• Strong data engineering foundations – SQL and NoSQL (Oracle, MongoDB), Kafka messaging, Elasticsearch or Gemfire for search and caching.
• Databricks or Snowflake, and modern data mesh / data product patterns.
• Ownership of test automation and CI/CD (JUnit, Mockito, Jenkins, Spinnaker), with accountability for application resiliency and security.
• Proven technical leadership in Agile teams – design ownership, code quality standards, and mentoring engineers.
• 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 considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

• AWS and containerization (Docker, Kubernetes).
• Front-end development for platform UIs (React JS, TypeScript).
• Delivery using approved AI tooling (GitHub Copilot, Claude).
• Hands-on delivery of data catalog, metadata, lineage or data governance capabilities on a regulated platform