To start, log into your Pipedrive account and navigate to the API section. Here, you'll find your API key, which is required to authenticate your requests. Note down the API key as you will use it to extract data from Pipedrive.

Log in to your AWS Management Console and create a new S3 bucket where you want to store the Pipedrive data. Ensure you set the appropriate permissions and configurations for your use case, such as enabling encryption and setting up bucket policies if needed.

Use Python to programmatically interact with the Pipedrive API. Install the `requests` library if you haven't already (`pip install requests`). Write a script to authenticate using your API key and fetch data (such as deals, contacts, or activities) from Pipedrive endpoints. Ensure your script handles pagination if you're extracting large datasets.

Example snippet:
```python
import requests

API_KEY = 'your_pipedrive_api_key'
endpoint = 'https://api.pipedrive.com/v1/deals?api_token=' + API_KEY

response = requests.get(endpoint)
data = response.json()
```

Once you've fetched the data, transform it into a format suitable for storage, such as JSON or CSV. You can use Python's built-in `json` module for JSON or `csv` module for CSV. This transformation step is important to ensure data integrity and compatibility with S3 storage.

Example for CSV:
```python
import csv

with open('pipedrive_data.csv', mode='w', newline='') as file:
writer = csv.writer(file)
# Assuming data is a list of dictionaries
writer.writerow(data[0].keys()) # Write header
for row in data:
writer.writerow(row.values())
```

Install and configure the AWS Command Line Interface (CLI) on your local machine if you haven't already. Use `aws configure` to set up your AWS credentials (Access Key ID and Secret Access Key) and default region. This setup is necessary for programmatically interacting with AWS services.

Use the AWS CLI to upload your transformed data file to the S3 bucket. The command will look something like this:

```bash
aws s3 cp pipedrive_data.csv s3://your-bucket-name/path/to/destination/
```

Ensure your IAM user has the necessary permissions to write to the specified S3 bucket.

To keep your S3 data updated, automate the script using a task scheduler. On Windows, you can use Task Scheduler, while on Linux, you can use cron jobs. This automation will help ensure your Pipedrive data is regularly backed up to S3 without manual intervention.

Example cron job entry:
```bash
0 0 * * * /usr/bin/python /path/to/your_script.py
```

By following these steps, you can effectively move data from Pipedrive to S3 without resorting to third-party connectors or integrations.