### 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)

)
        if not self.deferrable:
            self.log.info(
                "Fetching Data from %s.%s.%s max results: %s",
                self.table_project_id or hook.project_id,
                self.dataset_id,
                self.table_id,
                self.max_results,
            )
            if not self.selected_fields:
                schema: dict[str, list] = hook.get_schema(
                    dataset_id=self.dataset_id,
                    table_id=self.table_id,
                    project_id=self.table_project_id or hook.project_id,
                )
                if "fields" in schema:
                    self.selected_fields = ",".join([field["name"] for field in schema["fields"]])
            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,
                project_id=self.table_project_id or hook.project_id,
            )
            if isinstance(rows, RowIterator):
                raise TypeError(
                    "BigQueryHook.list_rows() returns iterator when return_iterator is False (default)"
                )
            self.log.info("Total extracted rows: %s", len(rows))