Crucial Exams

AWS Certified Data Engineer Associate DEA-C01 Practice Question

A data engineering team runs a daily batch pipeline that extracts data from Amazon RDS, transforms it with several AWS Glue Spark jobs, executes a data-quality AWS Lambda function, and then loads curated data into Amazon Redshift. The team needs orchestration that automatically retries transient failures with exponential backoff, persists state to avoid re-running completed steps, scales without infrastructure management, and offers native AWS service integrations. Which solution meets these requirements with the least operational overhead?

  • Define an AWS Glue workflow that chains the Glue jobs and uses triggers to invoke the Lambda function and Redshift data load steps.

  • Use Amazon EventBridge scheduled rules and target chaining to invoke each service sequentially, sending failed events to dead-letter queues.

  • Create an AWS Step Functions state machine that invokes the Glue jobs, Lambda function, and Redshift load through service-integrated tasks with retry and catch policies.

  • Deploy Amazon Managed Workflows for Apache Airflow (MWAA) and build a DAG that calls each service with Airflow operators and retry parameters.

AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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