Lead Software Engineer

JP Morgan Chase Bank; Jersey City (NJ); On-site; USD 140,000 - 170,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer to drive end-to-end data platform work within the AI/ML Data Platforms (AMDP) team in Jersey City. You will design, develop, test, deploy, and troubleshoot Java and Python services, data pipelines, and batch jobs, while ensuring performance, security, and reliability across enterprise-scale platforms.

The role demands strong full-stack capability, data processing expertise, modern front-end familiarity, and the ability to collaborate in a global,

Qualifications

• 5+ years of experience with formal training or certification on software engineering concepts.
• Hands-on experience in system design, application development, testing, and operational stability in production environments.
• Full stack development with Spring, Java, Python, Hibernate, Spark/PySpark, AWS, and Databricks.
• Experience with relational databases and SQL; familiarity with NoSQL databases and data modeling concepts.
• Ability to learn other coding languages and technologies.
• Knowledge of the data lifecycle including ingestion, validation, transformation, storage, governance and lineage, and consumption patterns.
• Ability to develop, debug, and maintain code in large enterprise environments with established controls and standards.
• Familiarity with CI/CD, observability and monitoring, and security best practices.
• Hands-on experience with AI-assisted software development tools and ability to critically evaluate AI outputs.
• Understanding of responsible AI use in engineering workflows.

Responsibilities

• Executes end-to-end software delivery including design, development, testing, deployment, and troubleshooting for Java & Python based services, batch jobs, and data pipelines.
• Has proficiency in data processing, APIs, scripting, and automation; focuses on performance, reliability, and testing.
• Familiar with modern front-end tech, especially React.JS & Angular.
• Produces design artifacts for complex workflows covering orchestration, processing logic, dependencies, and failure handling.
• Gathers and analyzes data to produce reports, metrics, and visualizations for business insights.
• Identifies data quality issues, drift, anomalies, and bottlenecks to drive improvements.
• Works in agile teams, globally with multiple time zones.
• Contributes to engineering communities, improves internal libraries, and evaluates emerging tech.
• Leverages AI-assisted tools to improve code quality, delivery speed, and productivity with peer review and secure coding.
• Applies SDLC tooling, Agile methodology, and automation to improve delivery speed.

Skills

Software engineering concepts

System design

Application development

Testing

Production operations

Spring

Java

Python

Hibernate

Spark/PySpark

AWS

Databricks

SQL

Relational databases

NoSQL

Data modeling

Adaptability

Data lifecycle

Ingestion

Validation

Transformation

Storage

Governance

Lineage

Debugging

Maintain code

CI/CD

Observability

AI-assisted development tools

Responsible AI

AWS certification

Git

Job description

Join AIML Data Platforms to help shape the future of AI/ML by building enterprise-scale data platforms that drive innovation across the firm.

As a Lead Software Engineer at JPMorganChase within the AI/ML Data Platforms (AMDP) - Data Governance Engineering team, you will spearhead the development and delivery of core Data capabilities as part of the AMDP platform that drive firm-wide innovation and excellence. In this role you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way.

Job Description

• Executes end-to-end software delivery including design, development, testing, deployment, and technical troubleshooting for Java & Python based services, batch jobs, and data pipelines
• Has strongproficiencyin data processing, APIs services, scripting, and automation using common libraries and frameworks relevant to the role. Attention to performance, reliability, and testing discipline
• Has familiarity with modern front-end technologies, especially in React.JS & Angular
• Produces design artifacts for complex workflows covering pipeline orchestration, processing logic, dependencyand failure handling, as well as in service-level objectives
• Gathers, analyzes, and synthesizes data to produce reports, metrics, and visualizations that support business and operational insights
• Identifieshidden problems and patterns in data and pipeline execution — including data quality issues, drift, anomalies, and bottlenecks — to drive system improvements
• Works individually or as part of a distributed agile team to deliver projects on time with strong ownership and accountability. Flexibility to work with a global team and multiple time-zones
• Contribute to engineering communities, improve internal libraries and utilities, and evaluate emerging technologies where appropriate
• Leverages enterprise-authorized AI-assisted software development tools to improve code quality, delivery speed, and productivity, whilevalidatingoutputs through peer review, automated testing, and secure coding standards
• Applies knowledge of tools within the Software Development Life Cycle toolchain, Agilemethodologyand automation capabilities, to improve delivery speed and the value realized by automation

Required qualifications, capabilities, and skills

• 5+ years of experience with formal training or certificationonsoftware engineering concepts.
• Hands‑on experience in system design, application development, testing, and operational stability in production environments
• Full stack development experience with Spring, Java, Python, Hibernate, Spark/PySpark, AWS cloud technologies, and Databricks
• Experience with relational databases and SQL; familiarity with NoSQL databases and data modeling concepts
• Ability to learn other coding languages and technologies as needed, with enthusiasm for continuous growth in both technical aptitude and business understanding
• Knowledge across the data lifecycle including ingestion, validation, transformation, storage, governance and lineage considerations, and consumption patterns
• Ability to develop, debug, andmaintaincode in large enterprise environments with established controls and standards
• Familiarity with continuous integration and delivery, application resiliency, security best practices, and observability and monitoring
• Hands‑on experience using enterprise-authorized AI-assisted software development tools withdemonstratedability to critically evaluate andvalidateAI-generated outputs
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations

Preferred qualifications, capabilities, and skills

• AWS Solutions Architect/Developer or advanced-level certification.
• Proficiencyacross the data management lifecycle.
• Skilled in resolving code issues and proficient in Git for managing repositories and team collaboration.