AWS Certified Data Engineer Associate DEA-C01 Practice Question

An e-commerce company stores hourly Apache Parquet files in an Amazon S3 prefix. A partner accepts only CSV files with a header row. About 5 GB arrives daily. The data engineer needs an automated, cost-effective pipeline that converts every newly created Parquet object to CSV and writes it to another S3 prefix. The team prefers minimal custom code and automatic scaling. Which approach meets these requirements?

  • Use Amazon S3 Event Notifications to invoke an AWS Lambda function that leverages the pandas library to download, convert, and upload each file in CSV format.

  • COPY the Parquet files into an Amazon Redshift staging table, then UNLOAD the data in CSV format to the target S3 prefix on a schedule managed by Amazon EventBridge.

  • Configure an Amazon Kinesis Data Firehose delivery stream with the S3 bucket as the source and enable record format conversion from Parquet to CSV.

  • Enable EventBridge for the S3 bucket and add a rule that starts an AWS Glue Studio ETL job. The job loads the Parquet object as a DynamicFrame and writes it as CSV with headers to the target prefix.

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