Begin by logging into your Snapchat Ads Manager account. Navigate to the 'Reports' section where you can access your campaign data. Customize your report by selecting the metrics, dimensions, and date range you need. Once satisfied, export the data in CSV format, as this is a widely supported file type.

On your local machine, ensure that you have Python installed, as it will be used to facilitate the data transfer. If it's not installed, download and install the latest version from the official Python website. Also, ensure that you have DuckDB installed in your Python environment. You can install DuckDB using pip with the command `pip install duckdb`.

Use Python to read the exported CSV file. You can use libraries like Pandas to load the CSV data into a DataFrame. First, install Pandas if you haven't already by executing `pip install pandas`. Then, use the following Python code to load the data:
```python
import pandas as pd

df = pd.read_csv('path/to/your/exported_file.csv')
```

Create a new DuckDB database or connect to an existing one using Python. DuckDB can operate entirely in-memory or use a file to store the database on disk. To create or connect to a database file, use the following code:
```python
import duckdb

conn = duckdb.connect('path/to/your/duckdb_file.db')
```

Based on the structure of your CSV data, create a table in DuckDB to store the imported data. Use a SQL command to define the table schema matching the CSV structure. You can execute the SQL command using DuckDB's connection:
```python
create_table_query = """
CREATE TABLE IF NOT EXISTS snapchat_data (
column1_name column1_type,
column2_name column2_type,
...
)
"""
conn.execute(create_table_query)
```

With the table created, insert the data from the Pandas DataFrame into the DuckDB table. DuckDB supports direct insertion from Pandas DataFrames. Execute the following command:
```python
conn.register('snapchat_df', df)
conn.execute('INSERT INTO snapchat_data SELECT * FROM snapchat_df')
```

After the data insertion, it's important to verify that the data has been correctly transferred. Run a few SELECT queries to check the data integrity:
```python
result = conn.execute('SELECT * FROM snapchat_data LIMIT 10').fetchall()
print(result)
```
Additionally, consider optimizing your DuckDB setup by analyzing the table or adding indices if necessary for your use case.

By following these steps, you can efficiently move data from Snapchat Marketing into DuckDB without relying on third-party connectors or integrations.