Apache Airflow version: 1.10.*
BackPort Packages version: 2020.10.29rc1

What happened:

BigQueryInsertJobOperator tries to start a BigQuery job by specifying a job_id which is a combination of dag_id, task_id, execution_date and an additional uniqueness_suffix.

https://github.com/PolideaInternal/airflow/blob/e5307990adb49a5a1c1c88a029940682efee0f9e/airflow/providers/google/cloud/operators/bigquery.py#L2073

However, it would appear that the regex pattern that is attempting to remove the `+` character is not correct as this still remain in `job_id` after `re.sub` is applied.

https://github.com/PolideaInternal/airflow/blob/e5307990adb49a5a1c1c88a029940682efee0f9e/airflow/providers/google/cloud/operators/bigquery.py#L2073

`Invalid job ID "airflow_my_test_dag_v1_test_2020_10_01T00_00_00+00_00_27f69de5cd17a012f3c89d414a70fe64". Job IDs must be alphanumeric (plus underscores and dashes) and must be at most 1024 characters long.
`  

How to reproduce it:

- Create a DAG with the name my-test-dag-v1.
- Run any query against BigQuery using this operator
airflow/providers/google/cloud/operators/bigquery.py
)
            gcp_conn_id = bigquery_conn_id
        self.dataset_id = dataset_id
        self.table_id = table_id
        self.max_results = int(max_results)
        self.selected_fields = selected_fields
        self.gcp_conn_id = gcp_conn_id
        self.delegate_to = delegate_to
        self.location = location
        self.impersonation_chain = impersonation_chain
    def execute(self, context) -> list:
        self.log.info(
            'Fetching Data from %s.%s max results: %s', self.dataset_id, self.table_id, self.max_results
        )
        hook = BigQueryHook(
            bigquery_conn_id=self.gcp_conn_id,
            delegate_to=self.delegate_to,
            impersonation_chain=self.impersonation_chain,
        )
        rows = hook.list_rows(
            dataset_id=self.dataset_id,
            table_id=self.table_id,
            max_results=self.max_results,
            selected_fields=self.selected_fields,
            location=self.location,
        )
        self.log.info('Total extracted rows: %s', len(rows))
        table_data = [row.values() for row in rows]
        return table_data
class BigQueryExecuteQueryOperator(BaseOperator):