KubernetesPodOperator  pod_template_file content doesn't support jinja airflow template variables. pod_template_file  is part of templated_fields list. 
https://github.com/apache/airflow/blob/master/airflow/providers/cncf/kubernetes/operators/kubernetes_pod.py#L165

template_fields: Iterable[str] = (        'image',        'cmds',        'arguments',        'env_vars',        'labels',        'config_file',        'pod_template_file',    )

But pod_template_file content is not supporting template variables. pod_template_file can be implemented the way SparkKubernetesOperator implemented using template_ext

https://github.com/apache/airflow/blob/master/airflow/providers/cncf/kubernetes/operators/spark_kubernetes.py#L46
 template_ext = ('yaml', 'yml', 'json')
airflow/providers/cncf/kubernetes/operators/kubernetes_pod.py
self, labels: dict, try_numbers_match: bool, launcher: Any, pod: k8s.V1Pod
    ) -> Tuple[State, Optional[str]]:
        """
        In cases where the Scheduler restarts while a KubernetesPodOperator task is running,
        this function will either continue to monitor the existing pod or launch a new pod
        based on the `reattach_on_restart` parameter.
        :param labels: labels used to determine if a pod is repeated
        :type labels: dict
        :param try_numbers_match: do the try numbers match? Only needed for logging purposes
        :type try_numbers_match: bool
        :param launcher: PodLauncher
        :param pod: Pod found with matching labels
        """
        if try_numbers_match:
            log_line = f"found a running pod with labels {labels} and the same try_number."
        else:
            log_line = f"found a running pod with labels {labels} but a different try_number."
        
        
        if self.reattach_on_restart and not pod.metadata.labels.get("already_checked"):
            log_line += " Will attach to this pod and monitor instead of starting new one"
            self.log.info(log_line)
            self.pod = pod
            final_state, result = self.monitor_launched_pod(launcher, pod)
        else: