**Apache Airflow version**: 2.0.0a2

**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): v1.15.12

**Environment**:
- **OS** (e.g. from /etc/os-release): CentOS 7


**What happened**:

When using KubernetesExecutor, a single SIGTERM doesn't result in the scheduler actually exiting cleanly. However, it will exit after receiving a second SIGTERM.

The same behavior happens if you have an exception in the scheduler. An easy way to replicate it is to raise in `pod_mutation_hook`.

In practice, this means the scheduler doesn't get restarted by K8s after encountering a exception. Or, when terminating the scheduler pod, it sticks around until k8s ultimately sends it a SIGKILL after its grace period is up.

**What you expected to happen**:

The scheduler to exit after a single SIGTERM.

**How to reproduce it**:
The easiest way to reproduce it is to simply send a SIGKILL to your KubernetesExecutor scheduler pod:

```
$ kubectl exec {scheduler_pod_name} kill 1
```

Note, the pod stays running, while the logs report:

```
[2020-10-30 17:34:09,581] {scheduler_job.py:794} INFO - Exiting gracefully upon receiving signal 15
[2020-10-30 17:34:10,586] {process_utils.py:97} INFO - Sending Signals.SIGTERM to GPID 59
[2020-10-30 17:34:10,879] {process_utils.py:63} INFO - Process psutil.Process(pid=59, status='terminated', exitcode=0, started=
'17:33:23') (59) terminated with exit code 0
[2020-10-30 17:34:10,882] {process_utils.py:97} INFO - Sending Signals.SIGTERM to GPID 59
[2020-10-30 17:34:10,882] {scheduler_job.py:1329} INFO - Exited execute loop
```

Issue another `kill`:
```
$ kubectl exec {scheduler_pod_name} kill 1
```

And the pod will be restarted by k8s.

If you can't reproduce it, let me know and I'll try and get something running on kind.

**Anything else we need to know**:

The same behavior happens if you have an exception in the scheduler. An easy way to replicate it is to raise in a `pod_mutation_hook`.


tests/jobs/test_scheduler_job.py
dagbag = DagBag(dag_folder="/dev/null", include_examples=True, read_dags_from_db=False)
        dag_file_processor = DagFileProcessor(dag_ids=[], log=mock.MagicMock())
        with create_session() as session:
            session.query(TaskInstance).delete()
            dag = dagbag.get_dag('example_branch_operator')
            task = dag.get_task(task_id='run_this_first')
            ti = TaskInstance(task, DEFAULT_DATE, State.RUNNING)
            session.add(ti)
            session.commit()
            requests = [
                TaskCallbackRequest(
                    full_filepath="A", simple_task_instance=SimpleTaskInstance(ti), msg="Message"
                )
            ]
            dag_file_processor.execute_callbacks(dagbag, requests)
            mock_ti_handle_failure.assert_called_once_with(
                error="Message",
                test_mode=conf.getboolean('core', 'unit_test_mode'),
            )
    def test_process_file_should_failure_callback(self):