Data engineers often spend their time building and maintaining data pipelines using classic ETL tools, which can be costly and inefficient. Modern data pipeline tools offer a more effective solution by automating these processes, allowing data engineers to focus on higher-value activities such as developing machine learning models and driving growth. As the demand for data engineers increases, companies must consider the return on investment of building their own data pipelines and prioritize staff morale and productivity.