Scenario: You need to rebuild your batch pipeline for structured data on Google Cloud. You currently use PySpark for large-scale data transformations, but the pipelines take over 12 hours to complete. You aim to speed up both development and pipeline execution using a serverless tool and SQL syntax. Your raw data is already stored in Cloud Storage. Question: How should you design your pipeline on Google Cloud to meet the requirements for faster development and processing?