Software Engineer III - Bigdata, Spark, AWS - Data Engineering

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 Corporate Technology, 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 breakdown technical problems
• Develop workflows and ETL data pipelines using Bigdata, Spark, AWS
• Build, test, and maintain scalable data pipelines and data architectures that support enterprise analytics use cases
• Apply data engineering best practices for performance optimization, reliability, and maintainability and Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• 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
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 7+ years applied experience
• Hands-on experience with Bigdata, Spark, AWS and SQL
• Knowledge of cloud platforms (AWS) and distributed data processing
• Hands-on practical experience in system design, application development, testing, and operational stability
• Ability to collaborate effectively within agile teams and across stakeholders
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• 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.
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

• Exposure to Databricks
• Exposure to cloud technologies

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.