Begin by ensuring your Apache Kafka 0.9 environment is properly set up and running. This involves having a Kafka broker and a Zookeeper instance. Ensure that data is being produced to Kafka topics as required. Use the `kafka-console-producer` and `kafka-console-consumer` for testing data flow within Kafka.

Create a Kafka consumer script using a compatible Kafka client library (like `kafka-python` for Python). This script will connect to your Kafka broker, subscribe to the desired topic, and read messages. You can start by using the following basic script structure:

```python
from kafka import KafkaConsumer

consumer = KafkaConsumer(
'your_topic',
bootstrap_servers=['localhost:9092'],
auto_offset_reset='earliest',
enable_auto_commit=True,
group_id='my-group')

for message in consumer:
print(message.value)
```

Modify this script to process the extracted data according to your needs.

Once data is extracted, transform it into a format suitable for Google Sheets. Typically, you will convert the message values into a CSV format or a list of dictionaries. This step might involve parsing JSON, cleaning data, or restructuring it.

Access the Google Cloud Console, create a new project, and enable the Google Sheets API. Generate credentials by creating a service account with the "Editor" role, and download the JSON file containing the private key. Share your desired Google Sheet with the service account email to allow access.

Install the Google Sheets API client library for Python to interact with Google Sheets. Use pip to install the necessary library:

```bash
pip install --upgrade google-api-python-client google-auth-httplib2 google-auth-oauthlib
```

Use the Google Sheets API client library to authenticate your script using the service account credentials and write data to your Google Sheet. Below is an example using Python:

```python
import gspread
from oauth2client.service_account import ServiceAccountCredentials

# Define the scope
scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]

# Add credentials to the account
creds = ServiceAccountCredentials.from_json_keyfile_name('path/to/your/credentials.json', scope)

# Authorize the clientsheet
client = gspread.authorize(creds)

# Get the instance of the Spreadsheet
sheet = client.open('your_google_sheet_name').sheet1

# Example: Write a list of data to a Google Sheet
data = [['Column1', 'Column2'], ['Value1', 'Value2']]
for row in data:
sheet.append_row(row)
```

Replace `'your_google_sheet_name'` and `'path/to/your/credentials.json'` with your actual Google Sheet name and credentials file path.

To automate data transfer, consider running the Kafka consumer script in a loop or setting it up as a scheduled job (e.g., using cron jobs on Linux). Ensure the script handles exceptions and retries connections to Kafka and Google Sheets to maintain robustness.

By following these steps, you can efficiently transfer and update data from Kafka 0.9 to Google Sheets without relying on third-party connectors or integrations.