**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`.


airflow/jobs/scheduler_job.py
unfinished_task_instances = (
                session.query(TI)
                .filter(TI.dag_id == dag_run.dag_id)
                .filter(TI.execution_date == dag_run.execution_date)
                .filter(TI.state.in_(State.unfinished))
            )
            for task_instance in unfinished_task_instances:
                task_instance.state = State.SKIPPED
                session.merge(task_instance)
            session.flush()
            self.log.info("Run %s of %s has timed-out", dag_run.run_id, dag_run.dag_id)
            
            self._update_dag_next_dagruns([session.query(DagModel).get(dag_run.dag_id)], session)
            callback_to_execute = DagCallbackRequest(
                full_filepath=dag.fileloc,
                dag_id=dag.dag_id,
                execution_date=dag_run.execution_date,
                is_failure_callback=True,
                msg='timed_out',
            )
            
            self._send_dag_callbacks_to_processor(dag_run, callback_to_execute)
            return 0
        if dag_run.execution_date > timezone.utcnow() and not dag.allow_future_exec_dates:
            self.log.error("Execution date is in future: %s", dag_run.execution_date)
            return 0
        if dag.max_active_runs:
            if (
                len(currently_active_runs) >= dag.max_active_runs
                and dag_run.execution_date not in currently_active_runs