**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
self.scheduler_job_job._schedule_dag_run(dr, {}, session)
        with create_session() as session:
            tis = session.query(TaskInstance).all()
        dags = self.scheduler_job_job.dagbag.dags.values()
        assert ['test_only_dummy_tasks'] == [dag.dag_id for dag in dags]
        assert 5 == len(tis)
        assert {
            ('test_task_a', 'success'),
            ('test_task_b', None),
            ('test_task_c', 'success'),
            ('test_task_on_execute', 'scheduled'),
            ('test_task_on_success', 'scheduled'),
        } == {(ti.task_id, ti.state) for ti in tis}
        for state, start_date, end_date, duration in [
            (ti.state, ti.start_date, ti.end_date, ti.duration) for ti in tis
        ]:
            if state == 'success':
                assert start_date is not None
                assert end_date is not None
                assert 0.0 == duration
            else:
                assert start_date is None
                assert end_date is None
                assert duration is None
        self.scheduler_job_job._schedule_dag_run(dr, {}, session)
        with create_session() as session:
            tis = session.query(TaskInstance).all()
        assert 5 == len(tis)
        assert {