Apache - Airflow : dag_id not not find on Kubernetes Executor worker pod!

I am new to Airflow and am thus facing some issues. I am working on Airflow, and have successfully deployed it on Celery Executor on AKS. Now I am trying to deploy Airflow using Kubernetes Executor on Azure Kubernetes Service. I am using the helm chart provided by tekn0ir for the purpose with some modifications to it. I used kubectl and managed to deploy it successfully. It has pods for scheduler, webserver, postgresql & dynamically created pods for running task-instances. For the purpose of synchronizing dags, I used a git-init container which successfully syncs dags on both scheduler as well as web server. However, when, I trigger a DAG, a new pod does get successfully created for running the task instance, but it throws error. I viewed the logs for that pod & found that the dags were probably not synchronized on the worker pods:
This is the error log for failed pod:

naman@IDC20Intern733:~/airflow-chart$ kubectl logs --v=3 -n airflow2 getpathi1-d5f07e2ec521471baa827bc82cf97a1e
[2020-06-25 11:16:10,309] {settings.py:213} INFO - settings.configure_orm(): Using pool settings. pool_size=5, max_overflow=10, pool_recycle=1800, pid=1
/usr/local/lib/python3.6/site-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use "pip install psycopg2-binary" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>.
  """)
[2020-06-25 11:16:10,480] {__init__.py:51} INFO - Using executor LocalExecutor
[2020-06-25 11:16:10,852] {dagbag.py:90} INFO - Filling up the DagBag from /opt/airflow/dags/getpath.py
Traceback (most recent call last):
  File "/usr/local/bin/airflow", line 32, in <module>
    args.func(args)
  File "/usr/local/lib/python3.6/site-packages/airflow/utils/cli.py", line 74, in wrapper
    return f(*args, **kwargs)
  File "/usr/local/lib/python3.6/site-packages/airflow/bin/cli.py", line 500, in run
    dag = get_dag(args)
  File "/usr/local/lib/python3.6/site-packages/airflow/bin/cli.py", line 146, in get_dag
    'parse.'.format(args.dag_id))
airflow.exceptions.AirflowException: dag_id could not be found: getpath. Either the dag did not exist or it failed to parse.

The pod description as executed is given below:

naman@IDC20Intern733:~/airflow-chart$ kubectl describe pod --v=4 -n airflow2 getpathi1-d5f07e2ec521471baa827bc82cf97a1e
Name:         getpathi1-d5f07e2ec521471baa827bc82cf97a1e
Namespace:    airflow2
Priority:     0
Node:         aks-nodepool1-41373778-vmss000001/172.19.0.35
Start Time:   Thu, 25 Jun 2020 16:46:05 +0530
Labels:       airflow-worker=f356d4e9-5dd2-4fe7-9974-712e9e2b3744
              airflow_version=1.10.10
              dag_id=getpath
              execution_date=2020-06-25T10_03_52.802506_plus_00_00
              kubernetes_executor=True
              task_id=i1
              try_number=1
Annotations:  <none>
Status:       Failed
IP:           172.19.0.50
IPs:          <none>
Init Containers:
  git-sync-clone:
    Container ID:   docker://2423801373d6d152461f5d68d87b20e4a87c27cd311c0c6646a9947c7cc6a7e4
    Image:          k8s.gcr.io/git-sync:v3.1.1
    Image ID:       docker-pullable://k8s.gcr.io/git-sync@sha256:aa701af5a29738f4a7aa1686f189787d92cea6401e0e81a170e98b10d365a949
    Port:           <none>
    Host Port:      <none>
    State:          Terminated
      Reason:       Completed
      Exit Code:    0
      Started:      Thu, 25 Jun 2020 16:46:06 +0530
      Finished:     Thu, 25 Jun 2020 16:46:08 +0530
    Ready:          True
    Restart Count:  0
    Environment:
      GIT_SYNC_REPO:      https://github.com/NamanBhat/dags
      GIT_SYNC_BRANCH:    master
      GIT_SYNC_ROOT:      /opt/airflow/dags
      GIT_SYNC_DEST:
      GIT_SYNC_DEPTH:     1
      GIT_SYNC_ONE_TIME:  true
      GIT_SYNC_REV:
      GIT_KNOWN_HOSTS:    false
    Mounts:
      /opt/airflow/dags from airflow-dags (rw)
      /var/run/secrets/kubernetes.io/serviceaccount from airflow2-token-bksdt (ro)
Containers:
  base:
    Container ID:  docker://bf5515c4cdd2c4d9e7cd12ececc9e79172abefe2d2f31c5a2f00fbc204c9dfad
    Image:         tekn0ir/airflow-docker:latest
    Image ID:      docker-pullable://tekn0ir/airflow-docker@sha256:e4b717801870d330487288b489b9b6462881bc038627b284cbead77fbe98c5cd
    Port:          <none>
    Host Port:     <none>
    Command:
      airflow
      run
      getpath
      i1
      2020-06-25T10:03:52.802506+00:00
      --local
      --pool
      default_pool
      -sd
      /opt/airflow/dags/getpath.py
    State:          Terminated
      Reason:       Error
      Exit Code:    1
      Started:      Thu, 25 Jun 2020 16:46:09 +0530
      Finished:     Thu, 25 Jun 2020 16:46:11 +0530
    Ready:          False
    Restart Count:  0
    Environment Variables from:
      airflow2-env  ConfigMap  Optional: false
    Environment:
      AIRFLOW__CORE__EXECUTOR:          LocalExecutor
      AIRFLOW__CORE__SQL_ALCHEMY_CONN:  postgresql+psycopg2://postgres:airflow@airflow2-postgresql:5432/airflow
      AIRFLOW__CORE__DAGS_FOLDER:       /opt/airflow/dags/
    Mounts:
      /opt/airflow/dags from airflow-dags (ro)
      /opt/airflow/logs from airflow-logs (rw)
      /var/run/secrets/kubernetes.io/serviceaccount from airflow2-token-bksdt (ro)
Conditions:
  Type              Status
  Initialized       True
  Ready             False
  ContainersReady   False
  PodScheduled      True
Volumes:
  airflow-dags:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
  airflow-logs:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
  airflow2-token-bksdt:
    Type:        Secret (a volume populated by a Secret)
    SecretName:  airflow2-token-bksdt
    Optional:    false
QoS Class:       BestEffort
Node-Selectors:  <none>
Tolerations:     node.kubernetes.io/not-ready:NoExecute for 300s
                 node.kubernetes.io/unreachable:NoExecute for 300s
Events:
  Type    Reason     Age    From                                        Message
  ----    ------     ----   ----                                        -------
  Normal  Scheduled  8m26s  default-scheduler                           Successfully assigned airflow2/getpathi1-d5f07e2ec521471baa827bc82cf97a1e to aks-nodepool1-41373778-vmss000001
  Normal  Pulled     8m25s  kubelet, aks-nodepool1-41373778-vmss000001  Container image "k8s.gcr.io/git-sync:v3.1.1" already present on machine
  Normal  Created    8m25s  kubelet, aks-nodepool1-41373778-vmss000001  Created container git-sync-clone
  Normal  Started    8m25s  kubelet, aks-nodepool1-41373778-vmss000001  Started container git-sync-clone
  Normal  Pulled     8m22s  kubelet, aks-nodepool1-41373778-vmss000001  Container image "tekn0ir/airflow-docker:latest" already present on machine
  Normal  Created    8m22s  kubelet, aks-nodepool1-41373778-vmss000001  Created container base
  Normal  Started    8m22s  kubelet, aks-nodepool1-41373778-vmss000001  Started container base

How can I resolve this issue, so that the DAGs get synchronized in worker pods at the right path and the tasks get executed in worker pods?

This is the link to the helm chart : https://github.com/tekn0ir/airflow-chart.
Thanks in advance

@Naman how did you resolve this issue? I am also seeing the same issue using Kubernetes Executor