Job Description

As a Software Engineer II-Python/PySpark at JPMorgan Chase within the Consumer and Community Banking Data Technology team, youserve 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 firms 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