Begin by exporting your data from Amazon Redshift to Amazon S3. Use the `UNLOAD` command which allows you to export data from Redshift tables into one or more text files in an S3 bucket. The command syntax is:
```sql
UNLOAD ('SELECT * FROM your_table')
TO 's3://your-bucket/your-folder/prefix'
CREDENTIALS 'aws_access_key_id=your_access_key;aws_secret_access_key=your_secret_key'
DELIMITER ','
ADDQUOTES
ALLOWOVERWRITE;
```
Ensure that your IAM role or credentials have the necessary permissions to write to the specified S3 bucket.

Once the data is unloaded to S3, verify that the files are present in the specified bucket and folder. Use the AWS S3 Console or AWS CLI command `aws s3 ls s3://your-bucket/your-folder/` to list the files and ensure they match your expectations.

In Snowflake, create an external stage that points to your S3 bucket. This stage will be used to load data into Snowflake. Execute the following SQL in Snowflake:
```sql
CREATE STAGE my_s3_stage
URL='s3://your-bucket/your-folder/'
STORAGE_INTEGRATION = my_integration;
```
Replace `my_integration` with a previously configured Snowflake storage integration that grants access to the S3 bucket.

Before loading data into Snowflake, create a table with the appropriate schema to hold the data. Use the `CREATE TABLE` command:
```sql
CREATE TABLE your_snowflake_table (
column1 STRING,
column2 STRING,
-- Add all necessary columns with their data types
);
```

Use the `COPY INTO` command to load data from the S3 stage into your Snowflake table. Execute the following command:
```sql
COPY INTO your_snowflake_table
FROM @my_s3_stage
FILE_FORMAT = (TYPE = 'CSV' FIELD_OPTIONALLY_ENCLOSED_BY = '"')
PATTERN = '.*[.]csv'; -- Adjust pattern if needed
```
This command tells Snowflake to read the CSV files from the S3 stage and copy them into the specified table.

After the data load is complete, verify that the data in Snowflake matches the data from Redshift. Run queries on your Snowflake table to ensure the integrity and completeness of the data.

Once you have confirmed that the data has been successfully transferred, you can clean up any temporary resources. This might include deleting the data files from S3 if they are no longer needed, and dropping the external stage in Snowflake if it won't be used again:
```sql
DROP STAGE my_s3_stage;
```
Use the AWS S3 console or CLI to delete the files from the specified S3 bucket.