As a Software Engineer II at JPMorgan Chase within the Chief Data Analytics Office - AIML Data Platforms Team, youare an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Solves the companys most challenging cloud data platform problems by building innovative technical solutions around Data Lake tools
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• Designs, implements, and maintains a managed AWS Databricks platform, and provides engineering and operational support for the platform to SRE and app teams.
• Performs platform design, set-up and configuration, workspace administration, resource monitoring, providing engineering support to data engineering teams, Data Science/ML, and Application/integration teams.
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
• 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

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 2+ years applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability
• Hands-on experience with Python and/or Java application program development with use of automated unit testing
• Hands-on experience with AWS services including provisioning infrastructure using automated tools
• Hands-on experience with GitHub / Bitbucket code versioning tool, Jenkins build tool and pypi / maven artifactory integrations
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Knowledge of Big Data distributed compute frameworks like Spark and Terraform
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.

Preferred qualifications, capabilities, and skills

• Hands-on experience with Big Data Spark Data Pipeline development
• Hands-on experience with Terraform Enterprise Infrastructure provisioning
• Hands-on experience with Databricks
• Knowledge of Platform Administration, Monitoring and Resiliency