Begin by logging into your Mailjet account. Navigate to the section where your email data is stored, such as the contact lists or campaign statistics. Most likely, you'll find an option to export this data. Choose the CSV format, as it is widely supported and easy to manipulate. Download the exported CSV file to your local system.

Open the exported CSV file using a spreadsheet application like Microsoft Excel or Google Sheets. Check for any data inconsistencies, such as missing values or incorrect data types. Ensure that the column headers are correctly named and match the intended schema you plan to use in Snowflake. Save any changes and ensure the file remains in CSV format.

Log into your Snowflake account. Create an internal stage where you will store the CSV file temporarily. Use the following SQL command in Snowflake's worksheet interface:
```sql
CREATE STAGE my_snowflake_stage;
```
This stage acts as a holding area for your file before loading it into a table.

Use the Snowflake web interface or SnowSQL command-line client to upload the CSV file to the created stage. If using SnowSQL, the command will look like this:
```bash
PUT file://path/to/your/file.csv @my_snowflake_stage;
```
This command uploads your local CSV file to the Snowflake stage for loading.

Define a table in Snowflake that matches the structure of your CSV file. Use the following SQL command:
```sql
CREATE TABLE my_mailjet_data (
column1_name column1_datatype,
column2_name column2_datatype,
...
);
```
Adjust the column names and data types to match those in your CSV file.

Load the data from the stage into the table by executing the following SQL command:
```sql
COPY INTO my_mailjet_data
FROM @my_snowflake_stage/file.csv
FILE_FORMAT = (TYPE = 'CSV' FIELD_OPTIONALLY_ENCLOSED_BY = '"');
```
This command reads the CSV file from the stage and inserts its contents into your Snowflake table.

Finally, verify that the data has been loaded correctly into your Snowflake table by running a simple query:
```sql
SELECT * FROM my_mailjet_data;
```
Check for data accuracy and completeness. Once confirmed, you can clean up by removing the file from the stage using:
```sql
REMOVE @my_snowflake_stage;
```

This guide outlines the steps to manually transfer data from Mailjet to Snowflake without using any third-party connectors or integrations, ensuring a direct and controlled data movement process.