### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

Using Apache Airflow 2.4.3 and apache airflow google provider 8.4 (also tried with 10.1.0).
We have a query that in production should run for a long time, so we wanted to make the BigQueryInsertJobOperator deferrable.
Making the operator deferrable runs the job, but the UI and triggerer process don't seem to be notified that the operator has finished.
I have validated that the query is actually run as the data appears in the table, but the operator gets stuck in a deferred state.

### What you think should happen instead

After the big query job is finished, the operator should exit it's deferred state.

### How to reproduce

Skeleton of the code used

```
with DAG(
    dag_id="some_dag_id",
    schedule="@daily",  
    catchup=False,
    start_date=pendulum.datetime(2023, 5, 8),
):
    extract_data = BigQueryInsertJobOperator(
        task_id="extract_data",
        impersonation_chain=GCP_ASTRO_TEAM_SA.get()
        params={"dst_table": _DST_TABLE, "lookback_days": _LOOKBACK_DAYS},
        configuration={
            "query": {
                "query": "{% include 'sql/sql_file.sql' %}",
                "useLegacySql": False,
            }
        },
        outlets=DATASET,
        execution_timeout=timedelta(hours=2, minutes=30),
        deferrable=True,
    )
```

### Operating System

Mac OS Ventura 13.3.1

### Versions of Apache Airflow Providers

apache airflow google provider 8.4 (also tried with 10.1.0).

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

We're using astro and on local the Airflow environment is started using `astro dev start`. The issue appears when running the DAG locally.
An entire other issue (may be unrelated) appears on Sandbox deployment.

### Anything else

Every time the operator is marked as deferrable.
I noticed this a few days ago (week started with Monday May 22nd 2023). 

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

self,
        project_id: str,
        dataset_id: str,
        table_id: str,
        rows: list,
        ignore_unknown_values: bool = False,
        skip_invalid_rows: bool = False,
        fail_on_error: bool = False,
    ) -> None:
        """Stream data into BigQuery one record at a time without a load job.
        .. seealso::
            For more information, see:
            https://cloud.google.com/bigquery/docs/reference/rest/v2/tabledata/insertAll
        :param project_id: The name of the project where we have the table
        :param dataset_id: The name of the dataset where we have the table
        :param table_id: The name of the table
        :param rows: the rows to insert
            .. code-block:: python
                rows = [{"json": {"a_key": "a_value_0"}}, {"json": {"a_key": "a_value_1"}}]
        :param ignore_unknown_values: [Optional] Accept rows that contain values
            that do not match the schema. The unknown values are ignored.
            The default value  is false, which treats unknown values as errors.
        :param skip_invalid_rows: [Optional] Insert all valid rows of a request,
            even if invalid rows exist. The default value is false, which causes
            the entire request to fail if any invalid rows exist.
        :param fail_on_error: [Optional] Force the task to fail if any errors occur.
            The default value is false, which indicates the task should not fail