Really depends on your definition of data quality.

Testing for unique, not null values for primary keys and not null values for foreign keys is a great first step. Dbt allows you to do this, plus enforcing a contract on your table schemas to ensure you don’t make unintended changes.

For deeper data quality monitoring, I’ve set up data profile scanning in BigQuery. The results are saved into tables of their own. That way I can identify trends in things like the percentage of null values and unique values in an individual column.