A data engineer needs to build a data pipeline to process medical records from 50...

Amazon Web Services Data-Engineer-Associate Question Answer

A data engineer needs to build a data pipeline to process medical records from 50 hospitals. The pipeline must ingest 5 GB of data from each hospital and remove personally identifiable information (PII). The pipeline must then transform the data and save the data in a central store. The pipeline must automatically retry after transient failures without manual intervention.

Which solution will meet these requirements with the LEAST operational overhead?

Store the data in Amazon S3. Use AWS Glue extract, transform, and load (ETL) jobs to process the data. Use AWS Glue DataBrew to remove the PII. Orchestrate the pipeline by using AWS Step Functions.

Deploy an Amazon EC2 instance to run a custom Python script to orchestrate the pipeline and remove the PII. Store the data in Amazon RDS. Use AWS Batch to process the data.

Store the data in Amazon S3. Create an AWS Lambda function to process the data and mask the PII. Configure Amazon EventBridge to orchestrate the pipeline.

Orchestrate the pipeline by using AWS Batch to remove the PII and transform the data. Store the data in Amazon S3.

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Update on: Jul 26, 2026
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