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Software Engineer II - Big Data (ETL) / DevOps Engineer + AWS
mid · Technology / Software Development
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.
Job responsibilities
- 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
- 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.