**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
"""
        If there are tasks left over in the executor,
        we set them back to SCHEDULED to avoid creating hanging tasks.
        :param session: session for ORM operations
        """
        if not self.executor.queued_tasks:
            return
        filter_for_ti_state_change = [
            and_(
                TI.dag_id == dag_id,
                TI.task_id == task_id,
                TI.execution_date == execution_date,
                
                
                TI._try_number == try_number - 1,  
                TI.state == State.QUEUED,
            )
            for dag_id, task_id, execution_date, try_number in self.executor.queued_tasks.keys()
        ]
        ti_query = session.query(TI).filter(or_(*filter_for_ti_state_change))
        tis_to_set_to_scheduled: List[TI] = with_row_locks(ti_query, session=session).all()
        if not tis_to_set_to_scheduled:
            return
        
        filter_for_tis = TI.filter_for_tis(tis_to_set_to_scheduled)
        session.query(TI).filter(filter_for_tis).update(
            {TI.state: State.SCHEDULED, TI.queued_dttm: None}, synchronize_session=False