Databricks

JPMorgan Chase & Co.•Wilmington, DE

About The Position

As a Lead Software Engineer - Python/PySpark/AWS/Databricks at JPMorganChase within Corporate & Enterprise Technology, you will drive the design, development, and deployment of robust technology solutions leveraging PySpark/Python, AWS, and Databricks. In this leadership role, you will manage a local team of developers, architect scalable systems, and uphold best practices across coding standards, testing, and cloud integration. You will partner closely with cross-functional teams to deliver high-performance applications and support mission-critical releases with strong quality and reliability.

Requirements

Formal training or certification in software engineering concepts and 5+ years of applied experience.
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Strong experience with PySpark/Python, AWS, and Databricks; exposure to machine learning
Data engineering experience
Proven project lead or team lead experience
Deep understanding of cloud architecture and distributed systems.
Excellent leadership, communication, and stakeholder management skills.
Ability to thrive in dynamic environments and navigate ambiguity.
Demonstrated track record of delivering enterprise-grade software solutions.

Nice To Haves

Advanced degree in Computer Science or a related field.
C++ development experience.

Responsibilities

Lead the design, development, and deployment of regulatory model applications and cloud modernization initiatives.
Architect and implement scalable, secure, and efficient solutions to process large data volumes.
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.
Collaborate with cross-functional teams to deliver projects on time and to high quality standards.
Contribute to strategic technology decisions and provide project/technical leadership.
Manage multiple priorities effectively in a fast-paced, dynamic environment.
Remain hands-on, contributing directly to implementation and technical delivery.