How to use our current Python ETL pipelines to populate and keep BigQuery tables in sync?

[faele]

How to use our current Python ETL pipelines to populate and keep BigQuery tables in sync?

• We have some ETL pipelines in Python that we use to populate a db (PostgresSQL) that we use for our reports (currently using Looker Studio).
• We want to direct some of these towards BigQuery to evaluate the possible replacement of Postgres with BigQuery.
• We do UPSERT operations every hour and every day we resynchronize the last day.
  Furthermore, it may happen that we have to resynchronize the database from the beginning of the year.
• Writing direct BigQuery upsert queries would be particularly expensive (every time the entire table size).
• We realized that Analytics historicizes by creating a subtable for each day.
• Can we use the same approach to connect our current ETL pipelines and update only 1 day?