### Apache Airflow Provider(s)

google

### Versions of Apache Airflow Providers

apache-airflow 2.5.0
apache-airflow-providers-apache-beam 4.1.0
apache-airflow-providers-cncf-kubernetes 5.0.0
apache-airflow-providers-google 8.6.0
apache-airflow-providers-grpc 3.1.0

### Apache Airflow version

2.5.0

### Operating System

Debian 11

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

KubernetesExecutor

### What happened

GCSToBigQueryOperator allows multiple ways to specify schema of the BigQuery table:

1. Setting autodetect == True
1. Setting schema_fields directly with autodetect == False
1. Setting a schema_object and optionally a schema_object_bucket with autodetect == False

This third method seems to be broken in the latest provider version (8.6.0) and will always result in this error:

```
[2022-12-16, 21:06:18 UTC] {taskinstance.py:1772} ERROR - Task failed with exception
Traceback (most recent call last):
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/providers/google/cloud/transfers/gcs_to_bigquery.py", line 395, in execute
    self.configuration = self._check_schema_fields(self.configuration)
  File "/home/airflow/.local/lib/python3.9/site-packages/airflow/providers/google/cloud/transfers/gcs_to_bigquery.py", line 524, in _check_schema_fields
    raise RuntimeError(
RuntimeError: Table schema was not found. Set autodetect=True to automatically set schema fields from source objects or pass schema_fields explicitly
```

The reason for this is because [this block](https://github.com/apache/airflow/blob/25bdbc8e6768712bad6043618242eec9c6632618/airflow/providers/google/cloud/transfers/gcs_to_bigquery.py#L318-L320) where `if self.schema_object and self.source_format != "DATASTORE_BACKUP":`. fails to set self.schema_fields. It only sets the local variable, schema_fields. When self._check_schema_fields is subsequently called [here](https://github.com/apache/airflow/blob/25bdbc8e6768712bad6043618242eec9c6632618/airflow/providers/google/cloud/transfers/gcs_to_bigquery.py#L395), we enter the [first block](https://github.com/apache/airflow/blob/25bdbc8e6768712bad6043618242eec9c6632618/airflow/providers/google/cloud/transfers/gcs_to_bigquery.py#L523-L528) because autodetect is false and schema_fields is not set.

### What you think should happen instead

No error should be raised if autodetect is set to False and a valid schema_object is provided

### How to reproduce

1. Create a simple BigQuery table with a single column col1:

```sql
CREATE TABLE `my-project.my_dataset.test_gcs_to_bigquery` (col1 INT);
```

2. Upload a json blob for this object to a bucket (e.g., data/schemas/table.json)
3. Upload a simple CSV for the source file to load to a bucket (e.g., data/source/file.csv)
4. Run the following command:

```py
    gcs_to_biquery = GCSToBigQueryOperator(
        task_id="gcs_to_bigquery",
        destination_project_dataset_table="my-project.my_dataset.test_gcs_to_bigquery",
        bucket="my_bucket_name",
        create_disposition="CREATE_IF_NEEDED",
        write_disposition="WRITE_TRUNCATE",
        source_objects=["data/source/file.csv"],
        source_format="CSV",
        autodetect=False,
        schema_object="data/schemas/table.json",
    )
```

### Anything else

_No response_

### 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)

by one or more columns. BigQuery supports clustering for both partitioned and
        non-partitioned tables. The order of columns given determines the sort order.
        Not applicable for external tables.
    :param autodetect: [Optional] Indicates if we should automatically infer the
        options and schema for CSV and JSON sources. (Default: ``True``).
        Parameter must be set to True if 'schema_fields' and 'schema_object' are undefined.
        It is suggested to set to True if table are create outside of Airflow.
    :param encryption_configuration: [Optional] Custom encryption configuration (e.g., Cloud KMS keys).
        **Example**: ::
            encryption_configuration = {
                "kmsKeyName": "projects/testp/locations/us/keyRings/test-kr/cryptoKeys/test-key"
            }
    :param location: [Optional] The geographic location of the job. Required except for US and EU.
        See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location
    :param impersonation_chain: Optional service account to impersonate using short-term
        credentials, or chained list of accounts required to get the access_token
        of the last account in the list, which will be impersonated in the request.
        If set as a string, the account must grant the originating account
        the Service Account Token Creator IAM role.
        If set as a sequence, the identities from the list must grant
        Service Account Token Creator IAM role to the directly preceding identity, with first
        account from the list granting this role to the originating account (templated).
    :param labels: [Optional] Labels for the BiqQuery table.
    :param description: [Optional] Description for the BigQuery table. This will only be used if the
        destination table is newly created. If the table already exists and a value different than the
        current description is provided, the job will fail.
    :param deferrable: Run operator in the deferrable mode
    """
    template_fields: Sequence[str] = (
        "bucket",