Begin by connecting to your MongoDB instance and extracting the data. You can use MongoDB's native tools such as `mongoexport` to export data from a collection into a JSON or CSV file. For example:
```bash
mongoexport --uri="your_mongodb_uri" --collection=your_collection --out=your_data.json
```
This command will export the specified MongoDB collection to a JSON file.

If you exported your data in JSON format, you will need to convert it to CSV since Snowflake can easily ingest CSV files. You can write a Python script or use a tool like `jq` to transform the JSON data to CSV format. Here's a basic example using Python:
```python
import json
import csv
with open('your_data.json') as json_file:
data = json.load(json_file)
with open('your_data.csv', mode='w', newline='') as csv_file:
writer = csv.writer(csv_file)
header = data[0].keys()
writer.writerow(header)
for row in data:
writer.writerow(row.values())
```

Log in to your Snowflake account and create a database and tables to hold the data. Use the Snowflake UI or SQL commands to set up your schema and tables according to the CSV structure. For example:
```sql
CREATE DATABASE my_database;
USE DATABASE my_database;
CREATE TABLE my_table (
field1 STRING,
field2 STRING,
field3 STRING
-- Add more fields as necessary
);
```

To load the CSV file into Snowflake, first, upload it to a Snowflake stage. This can be done using the Snowflake web interface or the SnowSQL command-line tool. Here’s how you can do it using SnowSQL:
```bash
snowsql -q "PUT file://path/to/your_data.csv @%my_table;"
```

Once the CSV file is staged, load the data into your Snowflake table using the `COPY INTO` command. This command reads data from the stage and inserts it into the table. For example:
```sql
COPY INTO my_table
FROM @%my_table/your_data.csv
FILE_FORMAT = (TYPE = 'CSV' FIELD_OPTIONALLY_ENCLOSED_BY = '"');
```

After loading the data, verify that it has been correctly inserted into the Snowflake table by running a simple `SELECT` query. This step ensures that the data integrity is maintained after the transfer:
```sql
SELECT * FROM my_table LIMIT 10;
```

To make this data transfer process repeatable, consider automating the steps using a script or a scheduling tool like cron (on Unix-like systems) or Task Scheduler (on Windows). This script should handle the extraction, transformation, upload, and loading steps, reducing manual intervention and potential errors.
By following these steps, you can efficiently move data from MongoDB to Snowflake without relying on third-party connectors or integrations.