Lead Software Engineer - Python, Data, Cloud

Lead Software Engineer - Python, Data, Cloud

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Markets Research Technology Team, your role will be pivotal in an agile team, tasked with the design and delivery of secure, robust, and cutting-edge technology products. You will be instrumental in implementing vital technology solutions across a range of technical domains and business functions to further the firm's business goals. Your contributions will be part of a high-profile data modernization project, where your duty will be to build a scalable cloud-native data platform in accordance with strategic modern data practices. Your responsibilities will also encompass the development of a core data platform, data products and data-intensive applications to advance the Research Technology business and client intelligence agenda. 

Job responsibilities

• Provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• 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.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Builds end-to-end modern data pipelines and solutions, migrating data products to cloud-native platforms
• Designs and implements data engineering solutions, leveraging cloud-native data technologies and aligning with modern data architecture strategies   
• Designs and implements hands-on solutions while providing technical leadership and mentorship to more junior team members
• Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude

Required qualifications, capabilities, and skills 

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering large-scale cloud-native data platforms
• Proficient in system design, application development, testing, and operational stability
• Advanced experience in one or more programming language(s) - Python/Java, and experience developing APIs and Backend services   
• 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
• Proven track record in system design, architecting and developing microservices, distributed systems and data-intensive applications
• Experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies        
• Practical experience developing Production-scale Cloud-native data engineering solutions in commercial environments   
• Familiarity with Cloud Data engineering services and technologies (e.g., ETL, Glue, S3, Athena, Redshift, Snowflake)     
• Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds 

Preferred qualifications, capabilities, and skills

• Experience with data and application migration to AWS in commercial settings
• Practical experience with Snowflake or Databricks 
• Familiarity with data quality, observability and lineage tooling
• Experience developing APIs and Backend services      
• Experience collaborating with data analysts, reporting teams or business analysts    
• Familiarity with modern Business Intelligence and reporting tools