Over the past year, a data engineering team focused on enhancing pipeline reliability and operational confidence by transitioning from a complex dependency management system using Airflow sensors to a more streamlined approach. Initially, the team used Airflow to scale rapidly, creating standardized pipeline templates for efficient task management. However, reliance on sensors led to frequent cascading failures and troubleshooting challenges. To address this, the team replaced sensors with Airflow asset scheduling, allowing automatic downstream DAG triggers upon successful completion of tasks, thereby simplifying recovery from failures. This shift, along with the introduction of a Control DAG for real-time visibility and Astro Observe for comprehensive pipeline health monitoring, reduced failure rates and improved operational efficiency. Astro Observe provided a more scalable solution by offering contextual insights and proactive alerts, allowing the team to prioritize fixes and maintain stakeholder alignment.