**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
other_dag = self.dagbag.get_dag('test_task_start_date_scheduling')
            other_dag.is_paused_upon_creation = True
            other_dag.sync_to_db()
            self.scheduler_job = SchedulerJob(executor=self.null_exec, subdir=dag.fileloc, num_runs=1)
            self.scheduler_job.run()
            
            assert len(session.query(TaskInstance).filter(TaskInstance.dag_id == dag_id).all()) == 0
            session.commit()
            assert [] == self.null_exec.sorted_tasks
            
            
            
            
            bf_exec = MockExecutor()
            backfill = BackfillJob(executor=bf_exec, dag=dag, start_date=DEFAULT_DATE, end_date=DEFAULT_DATE)
            backfill.run()
            
            assert len(session.query(TaskInstance).filter(TaskInstance.dag_id == dag_id).all()) == 1
            assert [
                (TaskInstanceKey(dag.dag_id, 'dummy', DEFAULT_DATE, 1), (State.SUCCESS, None)),
            ] == bf_exec.sorted_tasks
            session.commit()
            self.scheduler_job = SchedulerJob(dag.fileloc, executor=self.null_exec, num_runs=1)
            self.scheduler_job.run()
            
            assert len(session.query(TaskInstance).filter(TaskInstance.dag_id == dag_id).all()) == 1
            session.commit()
            assert [] == self.null_exec.sorted_tasks
    @pytest.mark.quarantined
    def test_scheduler_task_start_date(self):