Software Engineer III

Software Engineer III

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 III at JPMorgan Chase within Consumer & consumer banking, you are part of an agile team that enhances, designs, and delivers data collection, storage, access, and analytics solutions in a secure, stable, and scalable manner.

Job Responsibilities

• End-to-end data pipeline development.
• Design, implement, and maintain scalable batch and streaming pipelines for collecting, transforming, and delivering data across systems.
  Define, maintain, and evolve data models and curated datasets to support new use cases while ensuring quality, reliability, and timeliness.
• Data integration & movement
  Build secure, efficient solutions for moving data between systems (APIs, databases, files, and streams).
  Work with structured and unstructured data sources and apply best practices in orchestration and data modeling.
• Controls, data quality, and operational excellence
  Implement automated data quality checks and monitoring to improve pipeline reliability and readiness for controls/reporting use cases.
  Support governance expectations by producing clear documentation, data designs, and lineage/assumptions for technical and non-technical audiences.
• Collaboration & communication
  Work closely with product, engineering, and business teams to understand requirements and deliver solutions; document processes and share knowledge.
• 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.

Required qualifications, capabilities, and skills

• Experience in data engineering.
• Proven experience designing and building scalable data pipelines (ETL/ELT) for batch and streaming use cases using modern technologies such as AWS, PySpark, JavaSpark, Snowflake, Flink or Spark Streaming.
• Ability to work independently and collaboratively in a fast-paced, agile environment.
• Excellent communication and documentation skills.
• Knowledge of data governance, security, and compliance in financial services.
• Familiarity with CI/CD concepts, Git, and the end-to-end software delivery lifecycle.Tools & technologies (team stack),AWS, Snowflake, PySpark, JavaSpark, Ab Initio, Control-M, and Streaming solutions, Iceberg
• 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.