**Apache Airflow version**:

2.1.0

**Environment**:

- self hosted docker-compose based stack

**What happened**:

Using JDBCOperator if the sql result in an error we got only 
```
[2021-06-21 11:05:55,377] {local_task_job.py:151} INFO - Task exited with return code 1
```

Before upgrading from 2.0.1 we got error details in logs:
```
jaydebeapi.DatabaseError: java.sql.SQLException:... [MapR][DrillJDBCDriver](500165) Query execution error. Details: VALIDATION ERROR:...
``` 

**What you expected to happen**:

See `SQLException` in logs

**How to reproduce it**:

Perform a generic SQL task with broken SQL.

**Anything else we need to know**:

I think is somehow related to https://github.com/apache/airflow/commit/abcd48731303d9e141bdc94acc2db46d73ccbe12#diff-4fd3febb74d94b2953bf5e9b4a981b617949195f83d96f4a589c3078085959b7R202 
airflow/models/taskinstance.py
"""Prepare Task for Execution"""
        from airflow.models.renderedtifields import RenderedTaskInstanceFields
        task_copy = task.prepare_for_execution()
        self.task = task_copy
        def signal_handler(signum, frame):
            self.log.error("Received SIGTERM. Terminating subprocesses.")
            task_copy.on_kill()
            raise AirflowException("Task received SIGTERM signal")
        signal.signal(signal.SIGTERM, signal_handler)
        
        self.clear_xcom_data()
        with Stats.timer(f'dag.{task_copy.dag_id}.{task_copy.task_id}.duration'):
            self.render_templates(context=context)
            RenderedTaskInstanceFields.write(RenderedTaskInstanceFields(ti=self, render_templates=False))
            RenderedTaskInstanceFields.delete_old_records(self.task_id, self.dag_id)
            
            airflow_context_vars = context_to_airflow_vars(context, in_env_var_format=True)
            self.log.info(
                "Exporting the following env vars:\n%s",
                '\n'.join(f"{k}={v}" for k, v in airflow_context_vars.items()),
            )
            os.environ.update(airflow_context_vars)
            
            task_copy.pre_execute(context=context)
            
            self._run_execute_callback(context, task)
            if task_copy.is_smart_sensor_compatible():