Software Engineer III – PySpark/AWS/Databricks

What you'll do

• Builds and troubleshoots production software, algorithms, and data applications; creates architecture and design artifacts.
• Analyzes large datasets and uses findings to improve application quality, coding practices, and system architecture.
• Uses authorized AI coding tools to support development and automation, validates their outputs, and shares reusable practices.

What they ask for

• Formal training or certification in software engineering concepts and 3+ years of applied experience.
• Practical experience in system design, application development, testing, operational stability, and maintaining code in a large corporate environment.
• Experience with programming and database querying languages; strong SQL skills; experience with Python, PySpark, big data, data pipelines, or machine learning.
• Experience optimizing Spark clusters; hands-on AWS experience with EMR, EC2, S3, and CloudWatch; working knowledge of Databricks for data pipelines and machine-learning deployment.

Nice to have

• Familiarity with front-end technologies, AWS/Databricks, and Python machine-learning libraries such as Pandas and Numpy.
• AWS certifications or exposure to workflow orchestration tools such as Apache Airflow or Control M.

Tools

Python, PySpark, SQL, Spark, AWS, EMR, EC2, S3

AI focus

Uses enterprise-authorized AI-assisted development tools for coding, refactoring, tests, troubleshooting, documentation, and automation; critically validates outputs for correctness, performance, and security, and follows responsible-use practices.