Your customer data currently resides in an on-premises Hadoop cluster in Parquet format, with daily Apache Spark jobs handling data processing. You’re migrating both the data and Spark jobs to Google Cloud. Since future pipelines will leverage BigQuery, the data must be available there. Your goals include using managed services, minimizing changes to your existing ETL code, and keeping operational costs low. What is the best approach?