data-engineer-pro video for at Nexora Solutions , you're using Google Cloud Workflows to orchestrate a data pipeline that performs the following steps: Call an
At Nexora Solutions , you're using Google Cloud Workflows to orchestrate a data pipeline that performs the following steps: Call an external API that returns a 1KB JSON response . Apply complex business logic to the response. Wait for that processing to complete. Load data from a file in Cloud Storage into BigQuery . However, the Workflows standard library is insufficient to express your custom logic. You want to take advantage of Python's standard library instead. Your priority is to design a solution that is both simple to maintain and fast to execute. What is the best approach to meet these requirements?