Hi everyone, I recently moved into a Data Developer/Data Engineering role from a software development background, and I'm feeling a bit overwhelmed by the number of new technologies involved . The stack I'm working with includes BigQuery, DBT, Airflow, Git, and cloud-based data pipelines. I've started exploring the codebase and see things like models, macros, SQL files, YAML files, DAGs, and project structures, but I'm struggling to understand how everything fits together in a real-world workflow. I don't expect anyone to spoon-feed me, but I'd appreciate guidance from experienced engineers: • In what order should I learn these tools? • What concepts should I focus on first? • Their are any courses, YouTube channels, books, or projects you recommend? • How did you become productive with DBT, BigQuery, and Airflow when you first started? • If you had to start over today, what learning roadmap would you follow?…