Lead Software Engineer

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.

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 strong proficiency in 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, dependency and 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

Identifies hidden 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, while validating outputs through peer review, automated testing, and secure coding standards

Applies knowledge of tools within the Software Development Life Cycle toolchain, Agile methodology and 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 certification on software 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, and maintain code 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 with demonstrated ability to critically evaluate and validate AI-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.
• Proficiency across the data management lifecycle.
• Skilled in resolving code issues and proficient in Git for managing repositories and team collaboration.