The Vertex AI service account can assume the BigQuery Data Editor role to access resources across projects because this role grants the necessary permissions to read and write to datasets in BigQuery. This is particularly important for machine learning workflows, where training data is often stored in BigQuery, allowing seamless integration with Vertex AI for model training, evaluation, and prediction.
By utilizing the BigQuery Data Editor role, the Vertex AI service account can perform actions such as running queries, loading data for processing, and saving model outputs back into BigQuery datasets. This flexibility is crucial for data scientists and machine learning engineers who rely on BigQuery as a primary data source while training and deploying machine learning models.
The other options either do not provide sufficient permissions for the range of tasks needed in machine learning workflows or are not specifically designed for data manipulation in BigQuery. The Data Viewer role simply allows read access without the ability to modify datasets, the AI Engineer role is not a predefined IAM role, and the Viewer role has similar limitations to the Data Viewer role regarding resource modification.