The article outlines six key performance indicators (KPIs) that leaders should monitor throughout the data engineering lifecycle to improve efficiency and decision-making. These KPIs cover various aspects of data quality, productivity, and operational performance, providing a framework for evaluating the effectiveness of data engineering processes. By tracking these metrics, organizations can better align their data initiatives with business goals and enhance overall data strategy.