Data engineering, despite its importance, often operates with a "YOLO" (You Only Live Once) approach, where transformations are pushed straight to production without thorough testing. This can lead to wasted compute, slow iteration, pipeline lockups, and high costs of fixing defects. In contrast, CI/CD practices in software engineering ensure that every change is tested, integrated, and deployed in a structured, automated way. The article argues that data engineers need the same level of rigor as software developers to address the unpredictability of their dynamic environments. To bridge this gap, tools like dlt+ Cache aim to bring structured, repeatable testing to data engineering, enabling transformations to be tested locally before deployment and ensuring schema changes are validated instantly.