Begin by exporting your Trello data. Navigate to the Trello board you want to export, click on the "Show Menu" button, go to "More," and select "Print and Export." Choose the JSON format for export, as it preserves the data structure, making it easier to manipulate later.

Once you have your JSON file, you'll need to convert it to CSV, as Firebolt does not natively support JSON imports. Use a script or a tool like Python's `pandas` library to load the JSON data and convert it into a CSV format. The code snippet below demonstrates this process using Python:
```python
import pandas as pd
import json

with open('trello_data.json') as f:
data = json.load(f)

# Assume 'cards' is the relevant data needed from the JSON
df = pd.json_normalize(data['cards'])
df.to_csv('trello_data.csv', index=False)
```

Before importing data, ensure that your Firebolt database is set up and that you have the necessary permissions. Log into your Firebolt account, create a new database if needed, and ensure that the correct data warehouse is running.

Define a table in Firebolt to match the structure of your CSV data. Use the Firebolt SQL Editor to execute a SQL command to create a table. Make sure the data types in the table correspond to the fields in your CSV file.
```sql
CREATE TABLE trello_data (
id STRING,
name STRING,
desc STRING,
due DATE,
-- Add more columns as necessary
);
```

To upload the CSV file to Firebolt, you first need to upload the file to an accessible storage location like Amazon S3. From there, use Firebolt's COPY command to import the data into your table. Ensure your CSV is accessible and you have the correct credentials.
```sql
COPY INTO trello_data
FROM 's3://your-bucket/trello_data.csv'
CREDENTIALS = (aws_key_id = 'your-access-key' aws_secret_key = 'your-secret-key')
FILE_FORMAT = (TYPE = CSV, HEADER = TRUE);
```

After importing the data, run queries to verify that all records have been transferred correctly. Check for any discrepancies between the original Trello data and the data now in Firebolt. Use simple SELECT queries to perform these checks.

If this process needs to be repeated, consider scripting the entire workflow using a programming language like Python or a shell script. This script can automate the entire process from data export to import, ensuring efficiency for future data transfers.