### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

version 2.6.2

An error occurs when *.json is included in the parameters of BigQueryInsertJobOperator.
``` py
to_gcs_task = BigQueryInsertJobOperator(
        dag=dag,
        task_id='to_gcs',
        gcp_conn_id='xxxx',
        configuration={
            "extract": {
                 # The error occurred at this location.          
                "destinationUris": ['gs://xxx/yyy/*.json'],


                "sourceTable": {
                    "projectId": "abc",
                    "datasetId": "def",
                    "tableId": "ghi"
                },
                "destinationFormat": "NEWLINE_DELIMITED_JSON"
            }
        }
    )
```

error log 
```
jinja2.exceptions.TemplateNotFound: gs://xxx/yyy/*.json
```

### What you think should happen instead

According to the airflow.template.templater 
source : https://github.com/apache/airflow/blob/main/airflow/template/templater.py#L152
```py
      if isinstance(value, str):
            if any(value.endswith(ext) for ext in self.template_ext):  # A filepath.
                template = jinja_env.get_template(value)
            else:
                template = jinja_env.from_string(value)
            return self._render(template, context)
```

In the Jinja template source, if the value ends with .json or .sql, an attempt is made to read the resource file by calling jinja_env.get_template.

### How to reproduce

just call BigQueryInsertJobOperator with configuration what i added 

### Operating System

m2 mac

### 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)

assert {op4, op5} == set(op6.get_direct_relatives(upstream=True))
        assert {"label": "label1"} == dag.get_edge_info(
            upstream_task_id=op1.task_id, downstream_task_id=op2.task_id
        )
        assert {"label": "label2"} == dag.get_edge_info(
            upstream_task_id=op1.task_id, downstream_task_id=op3.task_id
        )
        
        [xlabel1, xlabel2] = [Label(label=f"xcomarg_label{i}") for i in range(1, 3)]
        [xop1, xop2, xop3, xop4, xop5, xop6] = [
            task_decorator(task_id=f"xcomarg_task{i}", python_callable=lambda: None, dag=dag)()
            for i in range(1, 7)
        ]
        chain(xop1, [xlabel1, xlabel2], [xop2, xop3], [xop4, xop5], xop6)
        assert {xop2.operator, xop3.operator} == set(xop1.operator.get_direct_relatives(upstream=False))
        assert [xop4.operator] == xop2.operator.get_direct_relatives(upstream=False)
        assert [xop5.operator] == xop3.operator.get_direct_relatives(upstream=False)
        assert {xop4.operator, xop5.operator} == set(xop6.operator.get_direct_relatives(upstream=True))
        assert {"label": "xcomarg_label1"} == dag.get_edge_info(
            upstream_task_id=xop1.operator.task_id, downstream_task_id=xop2.operator.task_id
        )
        assert {"label": "xcomarg_label2"} == dag.get_edge_info(
            upstream_task_id=xop1.operator.task_id, downstream_task_id=xop3.operator.task_id
        )
        
        [tg1, tg2] = [TaskGroup(group_id=f"tg{i}", dag=dag) for i in range(1, 3)]
        [op1, op2] = [BaseOperator(task_id=f"task{i}", dag=dag) for i in range(1, 3)]
        [tgop1, tgop2] = [
            BaseOperator(task_id=f"task_group_task{i}", task_group=tg1, dag=dag) for i in range(1, 3)
        ]