Software Engineer III-Python/PySpark

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 problemsLeverages 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 automationIdentifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systemsCollaborate closely with cross-functional teams to develop efficient data pipelines to support various data-driven initiativesImplement best practices for data engineering, ensuring data quality, reliability, and performanceContribute to data modernization efforts by leveraging cloud solutions and optimizing data processing workflowsPerform data extraction and implement complex data transformation logic to meet business requirementsMonitor and executes data quality checks to proactively identify and address anomaliesEnsure data availability and accuracy for analytical purposesIdentify 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 AWSExperience working with modern Data Lakes : (Snowflake, Databricks etc.)Hands-on practical experience delivering system design, application development, testing, and operational stabilityProficiency in automation and continuous delivery methodsWillingness and ability to learn and pick up new skillsetsHands-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 CycleAdvanced understanding of agile methodologies such as CI/CD, Application Resiliency, and SecurityDemonstrated 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 systemsPractical cloud native experience