Software Engineer III - Big Data / AWS

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorganChase within the Commercial & Investment Bank - Global Banking Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities 

• 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
• 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.
• 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. 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.
• 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
• 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
• Processing and analyzing large datasets using Big Data technologies, including Apache Spark, across data platforms comprising of Redshift, SQL DB, RDS and Databricks.
• Design, development, and implementation of scalable data pipelines and data matching solutions on AWS, utilizing Python/Java for data engineering tasks.
• Hands-on experience using enterprise-authorized AI-assisted software development tools such as GitHub and Copilot 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.
• Setup and Configuration of AWS services such as S3, Databricks, Step Functions, EMR, Glue, Lambda, RDS, EventBridge, Step-Functions and API Gateway for scripting, automation, and orchestration of data workflows.
• Development of semantic layer for data consumption using Iceberg tables and APIs.
• Implementation of continuous deployment and integration processes using Infrastructure as Code tools, including Terraform.
• Apply application, data, and infrastructure architecture disciplines to optimize data-intensive applications for performance and scalability.
• Troubleshoot and resolve issues related to application code and data workflows.

Preferred qualifications, capabilities, and skills 

• Familiarity with modern front-end technologies
• Exposure to cloud technologies