NEST Kenya Data Pipeline Optimization

Designed and optimized end-to-end ETL (Extract, Transform, Load) pipelines to efficiently manage and process national neonatal surveillance data. Leveraged modern data engineering practices to ensure high data quality, reliability, and scalability. Streamlined data workflows from multiple healthcare sources, enabling timely insights for monitoring neonatal health outcomes across Kenya. Technologies used included Python, PostgreSQL, Docker, and Airflow for automation, orchestration, and robust pipeline performance.

URL: https://github.com/franklinokech/cin_neonatal_data_pipeline