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 (., 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 (., 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 (., 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
