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Hi,
If I guess correctly you are using AWS Glue Studio and the AWS Glue big Query connector.
Currently the Glue Big query connector is working at table level (as the BigQuery Spark Connector does).
If you want to export all the tables in a dataset you may edit the script generated by Glue Studio and customize it.
you would first need to add the google.cloud python library using the method mentioned here.
then before you read the table, you read the list of tables in the dataset as described here.
Finally you iterate on the tables and you read/write them to S3.
This is one possibility the other would be to use an orchestrator as StepFunctions (an alternative could be Airflow), to run a python script to read the list of tables, and then execute the your job (once parametrized by tablename) in parallel for each table.
hope this helps
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