### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

Airflow version: 2.5.3
Description: While using BigQueryCreateExternalTableOperator, when we to create external table on top of parquet files located in GCS, airflow shows below error:
google.api_core.exceptions.BadRequest: 400 POST ... failed. CsvOptions can only be specified if storage format is CSV.

No csvOptions are mentioned while passing the source_format as Parquet. There seems to be an issue with bigquery.py hook.

### What you think should happen instead

_No response_

### How to reproduce

While using BigQueryCreateExternalTableOperator, try to create external table on top of parquet files located in GCS. Sample usage:
`create_external_table = BigQueryCreateExternalTableOperator(
    task_id="create_external_table",
    destination_project_dataset_table="table_name",
    bucket=GCS_BUCKET_NAME,
    source_objects=[<list of URIs of parquet files>],
    source_format="PARQUET",
    autodetect=True,
    gcp_conn_id="gcp_conn_id",
    google_cloud_storage_conn_id="test_conn_id",
)`

### Operating System

-

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### Anything else

_No response_

### 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)

encryption_configuration = {"key": "kk"}
        operator = BigQueryExecuteQueryOperator(
            task_id=TASK_ID,
            sql="Select * from test_table",
            destination_dataset_table=None,
            write_disposition="WRITE_EMPTY",
            allow_large_results=False,
            flatten_results=None,
            gcp_conn_id="google_cloud_default",
            udf_config=None,
            use_legacy_sql=True,
            maximum_billing_tier=None,
            maximum_bytes_billed=None,
            create_disposition="CREATE_IF_NEEDED",
            schema_update_options=(),
            query_params=None,
            labels=None,
            priority="INTERACTIVE",
            time_partitioning=None,
            api_resource_configs=None,
            cluster_fields=None,
            encryption_configuration=encryption_configuration,
        )
        operator.execute(MagicMock())
        mock_hook.return_value.run_query.assert_called_once_with(