Software Engineer II - Big Data (ETL) / DevOps Engineer + AWS

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 - Big Data (ETL) / DevOps Engineer + AWS at JPMorgan Chase within the Commercial & Investment Bank, you'll be a part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. 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.

Develop, enhance and test new/existing interfaces. The candidate will be part of existing agile team and will work on developing, enhancing ETL pipelines, design solutions Handle Dev Ops effort in terms of CICD, Scanning, Code, Performance testing and Test coverage Identify, analyze, and interpret trends or patterns in complex data sets and transforming existing ETL logic into AWS and Hadoop Platform Innovate new ways of managing, transforming and validating data 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 Establish and enforce guidelines to ensure consistency, quality and completeness of data assets Apply quality assurance best practices to all work products Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 2+ years applied experience Experience in AWS Services and DBx Experience in Athena,Redshift,Glue,Aurora,RDS,S3, Lambda and EC2 Experience in a Big Data technology (Hadoop and Spark Architecture, Performance tuning ,Spark SQL, Streaming, KAFKA, Entitlements etc., ) Experience in real time streaming data 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. Experience in Python is a must and Experience in writing SQL queries is a must Experience with LLMs integration, prompt/context engineering, AI Agent frameworks Strong Experience with UNIX shell scripting is must Experience in cloud platforms - AWS and DBx is a must and Familiarity with relational database environment (Oracle, SQL Server, etc.) leveraging databases, tables/views, stored procedures, agent jobs, etc. with strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy Preferred qualifications, capabilities, and skills Bachelor's degree in a technical or quantitative field with preferred focus on Information Systems Experience in Data bricks and Snowflake is preferred Experience of working in a development teams, using agile techniques and Object Oriented development and scripting languages, is preferred.