Backend Software Engineer III - Python/JAVA

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 Consumer & Community Banking (Data Products), 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.

You’ll be a seasoned agile engineer designing and delivering secure, stable, scalable data products and pipelines that power market-leading customer experiences.

span building modular Python services (reusable classes, logging, tests), distributed processing with PySpark, and modern ELT with dbt (macros, Jinja, seeds, custom tests).

You’ll orchestrate workloads with Airflow (MWAA/Astronomer/Kubernetes), develop on AWS (Glue, Athena, Lambda, CloudWatch), and automate infrastructure using Terraform.

You’ll work with lakehouse/open table formats (Iceberg/Hudi/Delta Lake) and Snowflake (streams, tasks, roles, warehouses), using Git, code reviews, and CI/CD.

Exposure to Kafka/Flink and familiarity with AI/ML concepts (LLMs, prompt engineering, evaluation, embeddings/vector search, responsible AI) are a plus.

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
• Build production-grade Python applications using modular design, reusable classes, structured logging, and automated testing.
• Develop and optimize ETL/ELT pipelines across batch and distributed compute environments (e.g., PySpark).
• Author and maintain dbt assets: macros, Jinja templates, seeds, and custom test cases to enforce data quality.
• Orchestrate workflows with Airflow (MWAA, Astronomer, or Kubernetes) and ensure reliable scheduling, retries, alerting, and runbook readiness.
• Implement AWS-based data processing patterns using Glue jobs, Athena, Lambda, and CloudWatch for monitoring/observability.
• Automate infrastructure provisioning and deployment workflows with Terraform.