Data Python Software Engineer III

JPMorganChase • Chicago, IL

1d

About The Position

As a Data Python Software Engineer III at JPMorganChase within the Commercial & Investment Bank Global Banking Technology team, you will serve as a seasoned member of an agile team, designing and delivering trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You will develop, test, and maintain critical data pipelines and architectures across multiple technical areas and business functions in support of the firm’s business objectives.

Requirements

• Formal training or certification in data engineering concepts and at least 3 years of applied experience.
• Hands-on Python coding experience and data analytics experience.
• Demonstrated experience using enterprise-authorized AI capabilities in a work environment to support data engineering workflows, with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs, such as query suggestions, test ideas, or model change summaries, before use; escalate when uncertain and follow data-handling requirements.
• Advanced SQL skills, including joins and aggregations, and a working understanding of NoSQL databases.
• Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns for analysis.
• Experience customizing changes in tools to generate product outputs and working with a Product Owner to analyze and interpret data.

Nice To Haves

• Hands-on experience with AWS.
• Familiarity with modern front-end technologies.

Responsibilities

• Support reviews of controls to ensure sufficient protection of enterprise data.
• Use enterprise-authorized AI capabilities to accelerate data pipeline and design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Make configuration and customization changes to generate products in response to business or customer requests, and advise colleagues on requests.
• Update logical or physical data models based on new use cases.
• Use SQL frequently and understand NoSQL databases and their role in the marketplace.
• Apply reuse-first, AI-assisted practices to strengthen SDLC quality routines for data pipelines, including test generation and control validation, while ensuring traceability, auditability, resiliency, and security alignment.
• Develop, test, and maintain critical data pipelines and architectures.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed