Develops secure, scalable software and data engineering solutions within an agile team. Responsibilities include designing and troubleshooting applications, building data pipelines and transformations, processing large datasets with big data frameworks, creating architecture artifacts, improving code and system resiliency, and using cloud-native AWS technologies. The role also requires responsible use and validation of AI-assisted development tools, collaboration in engineering communities, and adherence to secure coding and SDLC practices.
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 at JPMorgan Chase within the Consumer & Community Banking line of business, you will be part of an agile team responsible for designing, enhancing, and delivering software components for the firm’s state-of-the-art technology products, ensuring they are secure, stable, and highly scalable. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job responsibilities
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
- Adds to team culture of diversity, opportunity, inclusion, and respect
- 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
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- 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.
- Adds to team culture of diversity, Opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on Ab Initio or similar ETL tools and work experience is required
- Experience in Data Engineering disciplines such as data movement, data pipelines, data transformation, data storage and retrieval
- Experience with programming languages such as Java and Spark
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Expertise in one or more big data processing frameworks such as Spark, Flink, Storm, etc., as well as experience with stream processing using Kafka is mandatory
- Experience with Cloud services and cloud-native data technologies such as AWS EMR, Glue, Lambda
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Preferred qualifications, capabilities, and skills
- Familiarity with ETL, AWS, PySpark pipelines
- Exposure to cloud technologies
JPMorganChase Hyderabad, Telangana, IND Office
JP Morgan Tower, Salarpuria Sattva Knowledge City, HITEC City, Raidurgam, Hyderabad, Telangana, India, 500081
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