Job Description
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