Start by ensuring you have a Google Cloud project set up. You will need to enable the BigQuery and Firestore APIs for this project. Go to the Google Cloud Console, create a new project if necessary, and enable the necessary APIs under the "APIs & Services" section.

Define and execute the SQL queries in BigQuery to extract the data you need. Make sure your data is clean and formatted correctly for the intended Firestore structure. You can use the BigQuery console to run these queries and validate the data.

Use the BigQuery console or command-line tool to export your data to Google Cloud Storage. Save the results of your query as a CSV, JSON, or Avro file. This step involves specifying a Cloud Storage bucket where the exported data will be stored.

Example Command:
```
bq extract --destination_format=CSV 'your-project-id:your-dataset.your-table' gs://your-bucket-name/output-file.csv
```

In your Google Cloud project, set up a Firestore database in either Native or Datastore mode. Choose the mode based on your application requirements. Make sure to properly configure security rules if your data will be accessed by users.

Create a Google Cloud Function to read the exported data from Google Cloud Storage and write it to Firestore. Use the Node.js or Python client libraries for Firestore in your function. The function should parse the exported data file and iterate through each record to add it to Firestore.

Example Node.js Code Snippet:
```javascript
const { Storage } = require('@google-cloud/storage');
const admin = require('firebase-admin');
const functions = require('firebase-functions');

admin.initializeApp();
const storage = new Storage();
const firestore = admin.firestore();

exports.importData = functions.storage.object().onFinalize(async (object) => {
const bucket = storage.bucket(object.bucket);
const file = bucket.file(object.name);
const data = await file.download();
const records = JSON.parse(data.toString());

records.forEach(async (record) => {
await firestore.collection('your-collection').add(record);
});
});
```

Deploy the function using the Google Cloud Console or the gcloud command-line tool. Make sure to configure the function to trigger on file uploads to the specific Cloud Storage bucket where your data file is stored. Test the function by uploading a sample data file to ensure it correctly imports data into Firestore.

If you need to transfer data regularly, set up a cron job using Google Cloud Scheduler. Configure it to run a BigQuery query and export the results to Cloud Storage at regular intervals, triggering the Cloud Function each time. This setup will automate the data transfer process between BigQuery and Firestore.

Example gcloud Scheduler Command:
```
gcloud scheduler jobs create pubsub your-job-id --schedule="*/5 * * * *" \
--time-zone="your-time-zone" \
--topic=your-topic \
--message-body='{"message": "Run Data Transfer"}'
```

By following these steps, you can efficiently move data from BigQuery to Google Firestore using Google Cloud's native tools and services.