Automated Cloud-to-Cloud Pipeline

I developed an automated cloud-to-cloud data transfer system for a client who needed to move files from Google Cloud Storage into Amazon Web Services (AWS S3) without any manual steps. The goal was to build a reliable, daily pipeline that detects new datasets, organizes them by date, and transfers them directly into AWS S3 using a clean, timestamped folder structure.

The workflow I implemented scans the client’s Google Cloud bucket, identifies all CSV and Excel files, and pushes them into AWS S3 through a fully automated Python-based process. Each execution generates a new dated directory inside S3, ensuring the client’s data lake remains structured, consistent, and ready for BI or analytics workloads.

This solution eliminated the need for manual downloads and uploads, reduced operational workload, and established a continuous, stable data flow between cloud platforms. The pipeline now runs automatically each day without requiring client interaction, providing a scalable foundation