To begin, log in to your Mailchimp account and navigate to the list or campaign whose data you want to export. Use the export feature to download the data in a CSV format. This can usually be done by selecting the list, clicking "Export" from the list actions, and choosing the CSV option as the file format.

Once you have the CSV file, inspect it to ensure that it is correctly formatted and does not contain any corrupted data. Open the file in a spreadsheet application like Excel to verify column headers and data consistency. Make any necessary adjustments to ensure that the data structure aligns with the intended schema in Snowflake.

Log in to your Snowflake account and create a database and schema if they do not already exist. This can be done via the Snowflake web interface or using SQL commands. Use the following SQL command to create a database and schema if needed:
```sql
CREATE DATABASE mailchimp_data;
CREATE SCHEMA mailchimp_data.public;
```

Define a table in Snowflake that matches the structure of your CSV file. You will need to create SQL statements that describe the columns and data types. For instance:
```sql
CREATE TABLE mailchimp_data.public.subscribers (
email VARCHAR,
first_name VARCHAR,
last_name VARCHAR,
status VARCHAR,
signup_date DATE
);
```
Adjust the column names and data types according to your CSV file.

Use the Snowflake web UI or SnowSQL (Snowflake's command-line tool) to upload the CSV file to a Snowflake stage. First, create a named stage:
```sql
CREATE OR REPLACE STAGE my_csv_stage;
```
Then, use the PUT command to upload your CSV file to the stage:
```
snowsql -a -u -r -d mailchimp_data -s public -q "
PUT file://path/to/your/file.csv @my_csv_stage;"
```

With the CSV file staged, use the COPY INTO command to load the data into the Snowflake table:
```sql
COPY INTO mailchimp_data.public.subscribers
FROM @my_csv_stage/file.csv
FILE_FORMAT = (TYPE = 'CSV' FIELD_OPTIONALLY_ENCLOSED_BY = '"');
```
This command maps the data from the CSV to the table columns. Adjust the `FILE_FORMAT` clause if your CSV file uses different delimiters or enclosures.

After the import is complete, run a few SELECT queries on your Snowflake table to verify that the data is correctly loaded and matches the original CSV file. For instance:
```sql
SELECT FROM mailchimp_data.public.subscribers LIMIT 10;
```
This step ensures that the data has been accurately imported and is ready for further analysis or operations within Snowflake.

By following these steps, you should be able to successfully move data from Mailchimp to Snowflake without using any third-party connectors or integrations.