To interact with Zoom's data, you need to first set up API credentials. Log in to the Zoom Marketplace, create a new app, preferably a JWT (JSON Web Token) app for easy API access. Note down your API Key and Secret as you'll need them to authenticate requests to Zoom's API.

Determine which type of data you want to move from Zoom. This could be meeting recordings, participant details, or chat messages. Refer to Zoom’s API documentation to understand the endpoints and data structures related to your required data.

Develop a script using a programming language like Python. Use the `requests` library to make HTTP GET requests to Zoom API endpoints. Authenticate using your API Key and Secret, and fetch the data you identified in the previous step. Handle pagination if there's a large dataset.

Example:
```python
import requests

api_key = 'your_api_key'
api_secret = 'your_api_secret'
base_url = 'https://api.zoom.us/v2'

headers = {
'Authorization': f'Bearer {api_key}:{api_secret}'
}

def fetch_meeting_data(meeting_id):
url = f'{base_url}/meetings/{meeting_id}/recordings'
response = requests.get(url, headers=headers)
return response.json()

data = fetch_meeting_data('your_meeting_id')
```

Once your script retrieves the data, process it into a format suitable for S3 storage. This could involve converting JSON data to CSV or another format that matches your requirements. Use Python's `pandas` library for easy data manipulation and conversion.

Example:
```python
import pandas as pd

df = pd.json_normalize(data['recording_files'])
df.to_csv('zoom_data.csv', index=False)
```

Navigate to the AWS Management Console and create a new S3 bucket if you don't have one. Ensure that you configure appropriate permissions and policies to allow uploading files to the bucket.

Use the `boto3` library in Python to upload your processed data file to the S3 bucket. Set up your AWS credentials using the AWS CLI or by manually configuring the `boto3` session.

Example:
```python
import boto3

s3 = boto3.client('s3')
bucket_name = 'your-s3-bucket-name'
file_name = 'zoom_data.csv'

s3.upload_file(file_name, bucket_name, file_name)
```

After uploading, verify that the data is correctly stored in your S3 bucket. You can do this through the AWS Console by navigating to the S3 service and checking the contents of your bucket. Additionally, list objects programmatically to ensure the upload was successful.

Example:
```python
response = s3.list_objects_v2(Bucket=bucket_name)
for obj in response.get('Contents', []):
print(obj['Key'])
```

By following these steps, you can efficiently transfer data from Zoom to Amazon S3 without relying on third-party services.