Start by accessing the GNews API to extract the required data. You will need to sign up for an API key on the GNews website. Use this key to make HTTP GET requests to the GNews API endpoint relevant to your data needs, such as top headlines or search queries. Parse the JSON response to extract the data.

Once you have the JSON data, transform it into a CSV format. This can be done by iterating over the JSON objects and writing each news article's relevant fields (such as title, description, URL, etc.) into a CSV file. Use a script written in a language like Python with libraries such as `csv` to facilitate this process.

If you haven't already, create a Firebolt account and set up a database. Log in to the Firebolt console, create a new database, and define the schema that matches the structure of your CSV file. Ensure that the data types in the schema align with those in your CSV data.

Firebolt supports data ingestion from cloud storage services like Amazon S3. Upload your CSV file to a cloud storage bucket. Ensure that the file permissions allow Firebolt to access this file. Take note of the file path and access credentials.

In the Firebolt console, create an external table that points to your CSV file in cloud storage. Use the `CREATE EXTERNAL TABLE` command to define the table structure, specifying the column names, data types, and the location of the CSV file in your cloud storage.

After setting up the external table, create an internal table with the same schema. Use the `INSERT INTO` command to load data from the external table into the internal table. This step moves the data from your CSV file in cloud storage into Firebolt's high-performance storage.

Once the data is loaded into the internal table, perform a series of queries to verify the integrity and accuracy of the data. Check for any discrepancies or errors that might have occurred during the transformation or loading process. After verification, clean up by removing any unnecessary files from cloud storage to optimize storage costs.