DEA-C01 Question #272: Real Exam Question with Answer & Explanation

Question

A data engineer at a company is optimizing extract, transform, and load (ETL) workflows. The current architecture uses Amazon EMR and Apache Spark for large-scale transformations and AWS Glue for other ETL tasks. The workflows load processed data into an Amazon S3 based data lake. The company wants to move to a fully managed serverless solution that can orchestrate multiple ETL jobs and automate execution. The new solution must continue to use Spark to process data. The company needs to orchestrate and automate the ETL workflows with minimal manual intervention. Which solution will meet these requirements?

Options

• AMigrate all ETL jobs to AWS Glue. Use AWS Glue workflows to orchestrate the pipeline.
• BConfigure AWS Step Functions and Amazon EventBridge to orchestrate and invoke ETL
• CConfigure AWS Lambda functions to process Amazon S3 event notifications for data
• DUse Amazon Managed Workflows for Apache Airflow automatic scheduling to orchestrate the

Explanation

AWS Glue provides a fully managed serverless ETL service with native Spark support. By migrating all ETL jobs to Glue, the company eliminates the need to manage Amazon EMR clusters. Glue workflows can orchestrate and automate multiple ETL jobs, ensuring dependencies are respected and executions are automated with minimal manual intervention. This satisfies the requirement for a serverless, Spark-based, fully managed solution.

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