Google Cloud Professional Data Engineer Exam 2026 - Free Practice Questions and Study Guide

Using Cloud Composer to manage complex data workflows is the most suitable choice due to its design as a fully managed workflow orchestration service built on Apache Airflow. This service allows you to create, schedule, and monitor workflows that can integrate with various Google Cloud services and external systems seamlessly.

Cloud Composer enables users to define directed acyclic graphs (DAGs), which can represent complex workflows involving multiple tasks that need to be executed in a specific order. This capability is essential for data engineering tasks that require coordination, such as data ingestion, transformation, and loading across different data sources and destinations.

In contrast, Cloud Storage is primarily a storage solution and does not have built-in capabilities to orchestrate workflows. Google Functions is a serverless compute service that allows you to run simple functions in response to events, but it does not provide the necessary tooling for managing complex workflows that involve a series of interconnected tasks. BigQuery serves as a data warehouse optimized for analysis, while it can perform powerful queries, it does not have the orchestration features to manage data workflows effectively like Cloud Composer does.

Overall, Cloud Composer's orchestration features, ability to schedule workflows, and integration with various services make it the ideal choice for managing complex data workflows.