Software Engineer III - Java, Aws

JPMorgan Chase JPMorgan Chase · Banking · Mumbai, Maharashtra, India · Commercial & Investment Bank

Software Engineer III role at JPMorgan Chase focusing on designing and delivering technology products using Java and AWS. The role involves executing software solutions, creating production code, producing architecture artifacts, and analyzing data. A key aspect is leveraging enterprise-authorized AI coding assist tools to improve code quality and productivity, while also understanding and promoting responsible AI use.

What you'd actually do

  1. 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
  2. Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
  3. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
  4. Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
  5. Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Skills

Required

  • Software engineering concepts
  • AWS Services: S3, Glue, Redshift, Lambda, EMR
  • Java
  • Python
  • Data Modeling: Data Vault 2.0, Star, Snowflake schema, normalization
  • SQL
  • Data Quality & Governance
  • Databricks: Notebooks, Jobs, Delta Lake
  • AI-assisted software development tools

Nice to have

  • modern front-end technologies
  • cloud technologies

What the JD emphasized

  • Hands-on practical experience AWS Services: S3, Glue, Redshift, Lambda, EMR
  • Java, Python
  • Experience in Data Modeling: Data Vault 2.0, Star, Snowflake schema, normalization
  • SQL experience: Advanced querying, performance tuning
  • Experience in Data Quality & Governance: Validation frameworks, monitoring. Databricks: Notebooks, Jobs, Delta Lake
  • 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.