Software Engineer III - Backend / Data Engineer - Java, Python, Databricks

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

As a Software Engineer III (Java/Python Developer) at JPMorgan Chase within the Commercial and Investment Banking Emerging Markets Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading 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

• Partners with product and design teams to build functionality that meets core business outcomes.
• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Develops secure high-quality production code, and reviews and debugs code written by others.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
• Apply agile methodologies and use collaborative tools for effective teamwork and knowledge sharing.
• Implement and maintain unit and integration tests to ensure reliability and performance.
• Participate in code reviews to improve quality and share knowledge.
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge 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 applied experience in Core Java, J2EE, and Spring Boot with strong coding skills.
• Good working knowledge of AWS, Databricks and Python.
• Experience across the data lifecycle.
• Strong proficiency using Spring framework and understanding of inversion of control and dependency injection.
• Hands-on experience designing and implementing event-driven architectures with different message brokers, including Kafka.
• Experience creating RESTful microservices and handling asynchronous data.
• Experience integrating with both SQL Databases (Oracle) and No-SQL Databases (DynamoDB, MongoDB).
• Advanced at SQL, including joins and aggregations.
• Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns for analysis.
• Experience with Maven/Gradle.
• Experience using version control with GitHub/Bitbucket.
• Experience with modern testing tools (JUnit, Mockito, Spring Test Framework, Cucumber)
• Hands-on practical experience delivering application development, testing, and operational stability.
• Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• 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.

Preferred qualifications, capabilities, and skills

• Develop workflows and ELT pipelines using Python and Databricks.
• Familiarity with the Standardised data layer practices (Medallion architecture)
• Familiarity with modern backend technologies including Java 21+.
• Familiarity with Domain Driven Design as an approach to begin implementing system designs.
• Proficiency with AI code assistants for rapid prototyping and end delivery of Backend functionality.
• Experience with deploying Backend services to cloud providers (e.g. AWS, Google Cloud, Azure).
• Skills in designing efficient data models including normalization, denormalization, and schema design and an understanding around relational and star schemas