Built an end-to-end earthquake data pipeline using Python, SQL, and PostgreSQL to ingest, transform, and stage time-series data for reliable downstream analysis.
This project demonstrates a complete, production-aware data pipeline built to ingest, transform, and validate earthquake data for analytics and reporting use cases.

Rather than focusing solely on moving data from source to destination, this pipeline emphasizes the engineering fundamentals that make analytics trustworthy in real-world environments: data quality, repeatability, idempotent processing, and validation.

The result is a clean, analytics-ready staging dataset backed by SQL verification and designed with orchestration in mind.