AWS Certified Data Engineer Associate DEA-C01 Practice Question
A data engineer is building an AWS Glue job that reads raw files from an S3 data lake and loads the cleaned data into Amazon Redshift. Corporate security standards require role-based authentication and forbid storage of long-lived secrets in code or configuration. Which approach meets the requirement with the least operational overhead?
Attach an IAM role with the minimum required S3 and Amazon Redshift permissions to the AWS Glue job and rely on the role's temporary credentials at runtime.
Store an IAM user's access key and secret in AWS Secrets Manager and have the job retrieve them for S3 and Redshift access.
Add a bucket policy that grants public read access and keep using the default AWSGlueServiceRole without additional permissions.
Generate presigned S3 URLs for every required object and pass the URLs as job arguments so no IAM policies are needed.
Attaching an IAM role to the AWS Glue job provides true role-based authentication. When the job starts, AWS automatically issues temporary credentials for that role, so no static secrets are stored or rotated. Storing IAM user keys in Secrets Manager still depends on long-lived user credentials. Presigned URLs grant object-level S3 access only and do not cover Redshift, while continually regenerating them adds overhead. Making the bucket public contradicts the principle of least privilege and does nothing to authorize Redshift access.
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AWS Certified Data Engineer Associate DEA-C01
Data Security and Governance
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