Begin by exporting your required data from Harvest. Harvest provides CSV export options for various data like timesheets, invoices, and expenses. Navigate to the Harvest reports or data export section, select the data you need, and download it in CSV format. Ensure that you have access to the necessary data and permissions to perform exports.

Once the data is extracted, review the CSV files to ensure the data is clean and formatted correctly. Check for any inconsistencies, such as missing values or incorrect data types. If necessary, use a spreadsheet tool to clean, format, and validate the data before importing it into Snowflake.

Log into your Snowflake account and create a new database and schema to store the Harvest data. Use the Snowflake web interface or SQL commands to execute this step. For example, use:
```sql
CREATE DATABASE harvest_data;
CREATE SCHEMA harvest_data.public;
```

Before loading data, define the tables in Snowflake that will store your Harvest data. Use the structure of your CSV files to determine the table schema. Create tables using SQL DDL commands. For example, if you have a timesheets CSV, create a corresponding table:
```sql
CREATE TABLE harvest_data.public.timesheets (
id INTEGER,
user_id INTEGER,
project_id INTEGER,
hours DECIMAL(5, 2),
date DATE,
notes STRING
);
```

Upload the CSV files to a Snowflake stage. You can use the Snowflake web interface or SnowSQL CLI tool to accomplish this. First, create a stage if needed:
```sql
CREATE STAGE harvest_stage;
```
Then, use the `PUT` command from SnowSQL to upload the files:
```bash
PUT file://path/to/your/timesheets.csv @harvest_stage;
```

Use the `COPY INTO` command to load data from the stage into your Snowflake tables. This command will map the CSV data into the table structure you've defined:
```sql
COPY INTO harvest_data.public.timesheets
FROM @harvest_stage/timesheets.csv
FILE_FORMAT = (TYPE = 'CSV', FIELD_OPTIONALLY_ENCLOSED_BY = '"', SKIP_HEADER = 1);
```

After loading the data, it's crucial to verify and validate its integrity within Snowflake. Run queries to check for data consistency and accuracy. Ensure that all records have been imported correctly and compare them with the original CSV data. Adjust as needed by cleaning the data, adjusting the schema, or re-importing.

By following these steps, you can successfully move data from Harvest to Snowflake without the need for third-party connectors or integrations.