Worked on the omar-gamal99/talabat_bootcamp repository to enhance data pipeline automation and reliability using Airflow and Python. Developed a daily ETL DAG that executes a core extraction function, improving data freshness and reducing manual intervention. Introduced a master trigger DAG to centralize manual orchestration of key extract processes, streamlining operational workflows. Implemented dynamic DAG creation driven by YAML configuration files, enabling scalable and flexible DAG provisioning across environments. Addressed a scheduling issue by correcting the ETL DAG’s start date format, ensuring accurate execution timing. The work demonstrates a strong focus on maintainable data engineering and DevOps practices using Python and YAML.