**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
"""
        DagRuns with one unfinished and one failed root task -> RUNNING
        """
        
        
        dag_id = 'test_dagrun_states_root_fail_unfinished'
        dag = self.dagbag.get_dag(dag_id)
        dr = dag.create_dagrun(
            run_type=DagRunType.SCHEDULED,
            execution_date=DEFAULT_DATE,
            state=State.RUNNING,
        )
        self.null_exec.mock_task_fail(dag_id, 'test_dagrun_fail', DEFAULT_DATE)
        with pytest.raises(AirflowException):
            dag.run(start_date=dr.execution_date, end_date=dr.execution_date, executor=self.null_exec)
        
        
        with create_session() as session:
            ti = dr.get_task_instance('test_dagrun_unfinished', session=session)
            ti.state = State.NONE
            session.commit()
        dr.update_state()
        assert dr.state == State.RUNNING
    def test_dagrun_root_after_dagrun_unfinished(self):