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# Software Engineer III - Python/PySpark/Databricks/AWS

- **Company:** JPMorgan Chase & Co.
- **Location:** Wilmington, DE, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Software Applications, Automation of Tests, Unit Testing, Big Data, Code Generation, Software Quality, Computer Programming, Continuous Integration, Data Integration, Data Warehousing, Software Design Documents, DevOps, Python (Programming Language), Query Optimization, Standard Sql, DataOps, Secure Coding, Software Engineering, Systems Architecture, Toolchain, Large Language Models, Snowflake, Apache Spark, AI Coding Agents, Data Lakes, Pyspark, Production Code, AWS Glue, Data Analytics, Data Management, Amazon Simple Queue Service (SQS), Terraform, Data Pipelines, Databricks
- **Published:** October 16, 2026
- **Apply:** https://www.dice.com/job-detail/b2420b6e-5c13-4584-bba2-f20e83eb6a91

## About the Role

* Formal training or certification on software engineering concepts and 3+ years applied experience
 * Experience with Spark and SQL
 * Expertise in Lakehouse/Delta Lake architecture, system design, application development, testing, and ensuring operational stability
 * Strong programming skills in Python/PySpark, Databricks, AWS Glue, S3, SQS/SNS, Lambda etc., SQL
 * Proficient in orchestration using Airflow
 * In-depth knowledge of Big Data and data warehousing concepts
 * Experience with CI/CD processes
 * Solid understanding of agile methodologies, including DevOps practices, application resiliency, and security measures
 * Proven expertise in software applications and technical processes within a specialized technical domain
 * 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.

Preferred qualifications, capabilities, and skills

 * Familiarity with Snowflake, Terraform and LLM
 * Familiarity with Data Observability, Data Quality, Query Optimization & Cost Optimization
 * AWS certifications such as SAA, Associate Developer, Data Analytics Specialty, or Databricks certification

## Description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level., As an Software Engineer III - Python/PySpark/Databricks/AWS at JPMorgan Chase within the Corporate Sector-Global Finance team, you will be a key member of an agile team, tasked with designing and delivering cutting-edge products that are secure, stable, and scalable. Your role involves implementing essential technology solutions across diverse technical domains to support the firm's business goals effectively., * Developing and optimizing data pipelines and workflows to support data integration, transformation, and analysis

 * Implementing best practices for data management, ensuring data quality, security, and compliance
 * Writing secure, high-quality production code following AWS best practices, and deploying efficiently using CI/CD pipelines
 * Creating architecture and design documents for complex applications, ensuring software code meets design constraints
 * 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.
 * Identifying hidden issues and patterns in data to enhance coding practices and system architecture