
at J.P. Morgan
Bulge Bracket Investment BanksPosted 15 days ago
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**Lead Software Engineer (Python/Java/Spring/AWS)** As a Lead Software Engineer at JPMorganChase, drive secure, scalable tech solutions across agile teams. Key responsibilities include software design, development, and architecture using Python, Java, Spring, and AWS services like ECS, S3, and CloudWatch. Troubleshoot production issues, ensure software quality, and contribute to AI-assisted engineering practices. Leverage your 5+ years of experience, strong SQL skills, and proficiency in Jenkins, Terraform, and enterprise tools like Splunk, Dynatrace. Embrace agile methodologies and foster a culture of diversity and inclusion. Preferred: front-end tech familiarity, data pipeline and cloud migration experience.
- Compensation
- Not specified
- City
- Not specified
- Country
- United States
Currency: Not specified
Full Job Description
Location: Plano, TX, United States
As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking, Operations Technology, 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 firms business objectives.
Job responsibilities:
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- 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.
- Adds to team culture of diversity, equity, inclusion, and respect
- Detects, troubleshoots and Resolves Production issues in an Enterprise multi-environment settings using advanced observability tools
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficient in coding in one or more languages - Java, Python
- Proficient in private and public Cloud hosted Platform - Pivotal Cloud, AWS. In-depth knowledge is a must for AWS ECS, S3, SQS, SNS, Lambda, Glue, pySpark, cloudwatch
- Experienced in SRE and Observability tools - Splunk, Dynatrace and Datadog
- Proficient in Oracle, DB2 and AW Aurora Postgress Database. Hands on experience writing SQL is a must
- Hands on experience in Software Development tools and CI/CD tools - Jenkins, Spinnaker, IntelliJ, Bitbucket
- Hands on experience in IAC - Terraform
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Familiarity with modern front-end technologies
- Experience in Data Pipeline design and development
- Experience in Cloud migration projects
- Experience in AWS Glue and PySPark
- Overall knowledge of the Software Development Life Cycle




