### Apache Airflow Provider(s)

google

### Versions of Apache Airflow Providers

I'm using `apache-airflow-providers-google==8.2.0`, but it looks like the relevant code that's causing this to occur is still in use as of `8.8.0`.

### Apache Airflow version

2.3.2

### Operating System

Debian (from Docker image `apache/airflow:2.3.2-python3.10`)

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

Deployed on an EKS cluster via Helm.

### What happened

The first task in one of my DAGs is to create an empty BigQuery table using the `BigQueryCreateEmptyTableOperator` as follows:

```python
create_staging_table = BigQueryCreateEmptyTableOperator(
    task_id="create_staging_table",
    dataset_id="my_dataset",
    table_id="tmp_table",
    schema_fields=[
        {"name": "field_1", "type": "TIMESTAMP", "mode": "NULLABLE"},
        {"name": "field_2", "type": "INTEGER", "mode": "NULLABLE"},
        {"name": "field_3", "type": "INTEGER", "mode": "NULLABLE"}
    ],
    exists_ok=False
)
```
Note that `exists_ok=False` explicitly here, but it is also the default value.

This task exits with a `SUCCESS` status even when `my_dataset.tmp_table` already exists in a given BigQuery project. The task returns the following logs:

```
[2023-02-02, 05:52:29 UTC] {bigquery.py:875} INFO - Creating table
[2023-02-02, 05:52:29 UTC] {bigquery.py:901} INFO - Table my_dataset.tmp_table already exists.
[2023-02-02, 05:52:30 UTC] {taskinstance.py:1395} INFO - Marking task as SUCCESS. dag_id=my_fake_dag, task_id=create_staging_table, execution_date=20230202T044000, start_date=20230202T055229, end_date=20230202T055230
[2023-02-02, 05:52:30 UTC] {local_task_job.py:156} INFO - Task exited with return code 0
```

### What you think should happen instead

Setting `exists_ok=False` should raise an exception and exit the task with a `FAILED` status if the table being created already exists in BigQuery.

### How to reproduce

1. Deploy Airflow 2.3.2 running Python 3.10 in some capacity
2. Ensure `apache-airflow-providers-google==8.2.0` (or 8.8.0, as I don't believe the issue has been fixed) is installed on the deployment.
3. Set up a GCP project and create a BigQuery dataset.
4. Create an empty BigQuery table with a schema.
5. Create a DAG that uses the `BigQueryCreateEmptyTableOperator` to create a new BigQuery table.
6. Run the DAG from Step 5 on the Airflow instance deployed in Step 1.
7.  Observe the task's status.

### Anything else

I believe the silent failure may be occurring [here](https://github.com/apache/airflow/blob/main/airflow/providers/google/cloud/operators/bigquery.py#L1377), as the `except` statement results in a log output, but doesn't actually raise an exception or change a state that would make the task fail.

If this is in fact the case, I'd be happy to submit a PR, but appreciate any input as to any error-handling standards/consistencies that this provider package maintains.

### Are you willing to submit PR?

- [X] 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)

If provided all other parameters are ignored. External schema from object will be resolved.
    :param schema_object: If set, a GCS object path pointing to a .json file that
        contains the schema for the table. (templated)
    :param source_format: File format of the data.
    :param autodetect: Try to detect schema and format options automatically.
        The schema_fields and schema_object options will be honored when specified explicitly.
        https://cloud.google.com/bigquery/docs/schema-detect#schema_auto-detection_for_external_data_sources
    :param compression: [Optional] The compression type of the data source.
        Possible values include GZIP and NONE.
        The default value is NONE.
        This setting is ignored for Google Cloud Bigtable,
        Google Cloud Datastore backups and Avro formats.
    :param skip_leading_rows: Number of rows to skip when loading from a CSV.
    :param field_delimiter: The delimiter to use for the CSV.
    :param max_bad_records: The maximum number of bad records that BigQuery can
        ignore when running the job.
    :param quote_character: The value that is used to quote data sections in a CSV file.
    :param allow_quoted_newlines: Whether to allow quoted newlines (true) or not (false).
    :param allow_jagged_rows: Accept rows that are missing trailing optional columns.
        The missing values are treated as nulls. If false, records with missing trailing
        columns are treated as bad records, and if there are too many bad records, an
        invalid error is returned in the job result. Only applicable to CSV, ignored
        for other formats.
    :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud and
        interact with the Bigquery service.
    :param google_cloud_storage_conn_id: (Optional) The connection ID used to connect to Google Cloud
        and interact with the Google Cloud Storage service.
    :param delegate_to: The account to impersonate using domain-wide delegation of authority,
        if any. For this to work, the service account making the request must have
        domain-wide delegation enabled.