A major strength of a full-stack data engineer is the ability to bring the entire stack together, coordinating all of your microservices and features into a single product. Any developer can slap a new feature onto your project, but if new features aren't seamlessly integrated into your project as a whole, they will run inefficiently and slow down future development. See how everything can work together, from data pipeline to web app to data visualization and user-facing search functionality.
It is one thing to perform ETL on data originating from a single data source, but it is quite another to work with data coming in from different sources who have different APIs, different data formats, different error handling policies...and that's just the start. Check out this example of how to manage data coming in from separate origins, which in this case was different social media platforms.
After collecting your data, you are going to want to use it. In this project I demonstrate how to run batch jobs that audit content marketing websites for broken links, missed opportunities, and rooms for growth, all derived from Google Analytics and displayed in easy to use UIs.