Lead Software Engineer - Data Engineer [AWS, SQL, Python/Java]

JPMorganChase • Houston, TX

2d

About The Position

As a Lead Software Engineer in JPMorganChase’s Corporate Technology organization, you will contribute to an agile team that builds and enhances secure, stable, scalable technology products. You will deliver critical technology solutions across technical areas in support of business objectives, with a focus on data engineering, Python/Java, SQL, AWS, and Databricks.

The role includes designing and developing production-grade applications and data pipelines, supporting software in production, and applying sound engineering practices. You will also guide the team’s use of enterprise-authorized AI-assisted engineering tools, establish standards for validating AI-generated outputs, and coach engineers on responsible and secure use. You will identify opportunities to automate recurring remediation and improve operational stability, and help assess external vendors, startups, and internal solutions.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience.
• Strong data engineering experience, including Python, SQL, and AWS.
• Strong hands-on Python or Java development experience, including designing, building, and supporting production-grade applications and data pipelines.
• Strong SQL skills and experience with data processing and data engineering workloads.
• Hands-on experience with AWS services and building cloud-native solutions.
• Strong experience with Databricks, including development and processing of large datasets.
• Solid software engineering fundamentals and experience delivering and supporting production solutions.
• Demonstrated experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting.
• Ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations.
• Experience coaching engineers on safe, compliant adoption of AI-assisted tools within delivery practices.

Nice To Haves

• Proficiency in automation and continuous delivery methods, with strong SDLC discipline including CI/CD, testing, code quality, and release controls.
• Advanced understanding of agile delivery, application resiliency, and secure engineering practices.

Responsibilities

• Design, develop, and troubleshoot creative software solutions, addressing technical problems beyond routine approaches.
• Develop secure, high-quality production code and review and debug code written by others.
• Lead team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
• Establish consistent validation standards for AI-assisted work, including secure coding, peer review, and automated testing, and promote reuse of effective patterns.
• Apply SDLC toolchain capabilities, including authorized AI-assisted development and automation tools, to improve the value realized from automation.
• Identify opportunities to eliminate or automate recurring issues and improve software and system operational stability.
• Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and fit with existing systems and information architecture.
• Design, build, and support production-grade applications and data pipelines.

What This Job Offers

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