I published a public data engineering project that demonstrates a cloud-based ETL pipeline for analyzing web analytics search keyword revenue. The project uses PySpark, AWS Glue, Amazon S3, and Terraform to process hit-level web analytics data, extract external search engine domains and keywords, parse revenue, and generate a sorted reporting output. Key concepts covered: Batch ETL pipeline design PySpark transformations AWS Glue job configuration S3 input and output workflow Revenue aggregation logic Terraform infrastructure examples This is a generic open-source portfolio project and does not include proprietary or company-provided data. GitHub: https://github.com/naveenayalla1-CS50/search-keyword-performance-revenue Feedback from data engineers and cloud data practitioners is welcome.