You're ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you. As a Software Engineer II-Python/PySpark at JPMorgan Chase within the Consumer and Community Banking Data Technology team, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions 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 firm's business objectives. Job responsibilities Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems 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 Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Collaborate closely with cross-functional teams to develop efficient data pipelines to support various data-driven initiatives Implement best practices for data engineering, ensuring data quality, reliability, and performance Contribute to data modernization efforts by leveraging cloud solutions and optimizing data processing workflows Perform data extraction and implement complex data transformation logic to meet business requirements Monitor and executes data quality checks to proactively identify and address anomalies Ensure data availability and accuracy for analytical purposes Identify opportunities for process automation within data engineering workflows Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 2+ years applied experience. Experience with ETL tools like Data Pipeline and workflow management tools (Airflow, etc.) Hands on coding experience with PySpark, Python, Iceberg ,AI and AWS Experience working with modern

Data Lakes :

(Snowflake, Databricks etc.) Hands-on practical experience delivering system design, application development, testing, and operational stability Proficiency in automation and continuous delivery methods Willingness and ability to learn and pick up new skillsets 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 Advanced in one or more programming language(s) like SQL, Java etc. Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning etc.) In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience