Built a scalable cloud ETL pipeline using Python, PostgreSQL, Pandas, and Docker to efficiently process, clean, and load over 1.6 million records with optimized batch processing, fault tolerance, and automated data validation.
End-to-end Data Engineering portfolio covering ETL, streaming, fraud detection, and financial analytics across M-Pesa, KCB, Equity Group, Absa, and KRA — with live Streamlit dashboards.
Real-time data streaming pipeline built with modern data engineering tools for scalable ingestion, processing, transformation, and analytics of continuous data streams.