Pre-scheduled DBT Airflow DAGs

• Supported schedules (one DAG per schedule) are daily, weekly, monthly.
• All DAGs read dbt model configuration from the same config directory
• Each team has their own team_name.yaml configuration file where they specify the dbt models they want to run
• The YAML configuration for each DAG should require at least these configuration fields, plus any other optional fields:
  • job_name which will become a task name within the Airflow DAG
  • schedule - one of daily, weekly, monthly which determines which DAG that job will go to
  • models and/or tags - lists of selector values that will determine what the dbt run command actually runs for that specific task
  • depends_on - a list of dataset names from datasets.yaml the dbt model run depends on (will get materialized as sensor operators)
• Within each DAG, if there are one or more tasks from a particular team then all those tasks will be in an Airflow TaskGroup bearing that team's name

Closes T419925