After some investigation of GCP documentation, I have found a solution. So I’ve found the following flow.

Scheduled queries on a daily basis check the BigQuery table using the above-mentioned query. In case the table is empty, a scheduled query publishes a message to GCP Pub/Sub. GCP Cloud Function written using Python listens to the Pub/Sub cloud event, and if there is a new message in Pub/Sub, it consumes a message and publishes it to the corresponding Slack channel.

What should be done:

1. Create a Pub/Sub topic using Terraform
2. Create a Scheduled query using Terraform
3. Create a Cloud Function using Python
4. Create a Deployment for Cloud Function using GitHub Actions

Pub/Sub topic using Terraform

resource "google_pubsub_topic" "topic-name" {
          
 name    = "pubsub-topic-name"
          
 project = var.project_id
        
}

Сreate a Scheduled query using Terraform

resource "google_bigquery_data_transfer_config" "scheduled_query_name {
                  
 depends_on = [module.bigquery_dataset]
                
                  
 display_name         = "Check if BigQuery table is not populated"
                  
 location             = var.euw4_region
                  
 service_account_name = module.service_account_name.email
                  
 data_source_id       = "scheduled_query"
                  
 schedule             = "every day 08:00"
                  
 params = {
                    
 query = "ASSERT NOT EXISTS(SELECT COUNT(*) FROM `${var.project_id}.${local.dataset_name}.${local.table_name}` where DATE(UPDATED_AT) < DATE(CURRENT_TIMESTAMP())) AS "Table has no records""
                }
 notification_pubsub_topic = "projects/${var.project_id}/topics/topic_name"
                  project                   = var.project_id
                
 }

Create a Cloud Function using Python

import base64
    
import functions_framework
    
import os from slack_sdk 
import WebClient
    
    

slack_token = os.environ["SLACK_TOKEN"]
    
client = WebClient(token=slack_token)
    
    

@functions_framework.cloud_event
    
def process_pubsub_message(event):
        
    data: Dict = event.data
               
    slack_text = base64.b64decode(data["message"]["data"]).decode('utf-8')   
    slack_channel_id="your_channel_id"
        
    client.chat_postMessage(channel=slack_channel_id, text=slack_text)

Create a Deployment for Cloud Function using GitHub Actions

gcloud functions deploy "${{ env.CLOUD_FUNCTION_NAME }}" 
        
--region "${{ env.REGION }}" 
        
--entry-point process_pubsub_message 
        
--gen2 
        
--runtime python312 
        
--timeout 60s 
        
--project ${{ vars.GCP_PROJECT_ID }} 
        
--service-account your-service-account-sa@${{ vars.GCP_PROJECT_ID }}.iam.gserviceaccount.com 
        
--build-service-account projects/${{ vars.GCP_PROJECT_ID }}/serviceAccounts/your-service-account-sa@${{ vars.GCP_PROJECT_ID }}.iam.gserviceaccount.com 
        
--run-service-account your-service-account-sa@${{ vars.GCP_PROJECT_ID }}.iam.gserviceaccount.com 
        
--source ./CloudFunction 
        
--trigger-topic topic-name 
--set-env-vars SLACK_TOKEN=${{ secrets.SLACK_TOKEN }}

Also not to forget to define SLACK_TOKEN in secrets