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Q1AWS Certified Data Engineer Associate
Q1. An insurance company compiles each policyholder’s daily premium payment records into CSV format and stores them in an Amazon S3 bucket.
A data engineer uses an AWS Glue crawler to crawl this S3 data.
The data engineer must keep the S3 data available in the AWS Glue Data Catalog every day.
Which solution meets this requirement?
Show answer
Correct answer: B. Create an IAM role with the AWSGlueServiceRole policy and associate it with the crawler. Specify the S3 bucket path of the source data as the crawler’s data store. Schedule the crawler to run daily, and specify a database name as the output target.
The correct answer is B.For a crawler’s IAM role, using the AWSGlueServiceRole policy, which bundles the permissions required for Glue operations, is the standard configuration, whereas excessive permissions such as AmazonS3FullAccess violate the principle of least privilege.
In addition, because a crawler’s results are written to a database within the AWS Glue Data Catalog, the output target must specify a database name rather than an S3 bucket path.
Allocating data processing units (DPUs) is a setting related to ETL jobs and is not required to run a crawler itself.
Therefore, options A, C, and D all fail to meet the requirement.
AWS Glue: Create an IAM role for the crawler (AWS official documentation)
Q2AWS Certified Data Engineer Associate
Q2. A retail company loads store-level sales transaction data into an Amazon Redshift table after business hours every night.
The company wants to be able to determine which tables have been loaded and which tables have not.
A data engineer wants to store the details of the Redshift table load status in an Amazon DynamoDB table.
The data engineer created an AWS Lambda function that publishes the load status details to DynamoDB.
How should the data engineer invoke this Lambda function so that the load status is written to the DynamoDB table?
Show answer
Correct answer: B. Use the Amazon Redshift Data API to publish an event to Amazon EventBridge, and configure an EventBridge rule that invokes the Lambda function on that event.
The correct answer is B.Because the Amazon Redshift Data API can automatically publish events, such as query completion, to Amazon EventBridge, a configuration that triggers the Lambda function directly with an EventBridge rule is the approach with the lowest operational overhead.
Routing through an SQS queue (option C) is technically possible as well, but it requires additional polling and configuration and is not efficient.
Monitoring CloudWatch or CloudTrail events with a second Lambda function (A, D) makes the configuration more complex and makes it harder to capture the exact timing of load completion, so these are not appropriate.
About the Amazon Redshift Data API (AWS official documentation)
Q3AWS Certified Data Engineer Associate
Q3. A manufacturing company needs to securely transfer 5 TB of design and manufacturing records, which are stored in its on-premises data center, to an Amazon S3 bucket.
Approximately 5% of the data is updated daily.
The updates must be reflected in the S3 bucket on a regular basis.
The data includes files in multiple formats.
The data engineer needs to automate the transfer process and schedule it to run periodically.
Which AWS service should the data engineer use to transfer the data with the greatest operational efficiency?
Show answer
Correct answer: A. AWS DataSync
The correct answer is A.AWS DataSync is a service that automates data transfer between on-premises and AWS storage and can efficiently sync only incremental data, and it also provides scheduled execution and support for multiple file formats as standard features.
AWS Glue is a service whose main purpose is data cataloging and ETL processing, and it is not suited for transferring large volumes of data.
AWS Direct Connect provides a dedicated network connection and does not include mechanisms for automating or scheduling transfers.
S3 Transfer Acceleration is intended to speed up single-file uploads and is not suited for incremental sync.
What is AWS DataSync (AWS official documentation)
Q4AWS Certified Data Engineer Associate
Q4. A manufacturing company uses an on-premises Microsoft SQL Server database to store financial transaction data.
The company migrates the transaction data from the on-premises database to AWS at the end of every month.
The company has noticed that the cost of migrating from the on-premises database to an Amazon RDS for SQL Server database has recently increased.
The company needs a cost-effective solution for migrating the data to AWS.
The solution must minimize downtime for applications that access the database.
Which AWS service should the company use to meet these requirements?
Show answer
Correct answer: B. AWS Database Migration Service (AWS DMS)
The correct answer is B.AWS DMS is a service specialized in database migration, and its continuous replication capability enables cost-effective migration while minimizing downtime.
AWS Lambda is a general-purpose serverless execution environment and does not provide features dedicated to database migration.
AWS Direct Connect is a dedicated network connection service and has no capability to perform data migration itself.
AWS DataSync mainly targets data transfer between file storage and is not suited for migrating relational databases.
AWS Database Migration Service User Guide (AWS official documentation)
Q5AWS Certified Data Engineer Associate
Q5. A healthcare company is building a data pipeline on AWS using AWS Glue extract, transform, and load (ETL) jobs.
A data engineer needs to process and transform data from Amazon RDS and MongoDB and load the transformed data into Amazon Redshift for analytics.
The data must be updated every hour.
Which combination of tasks meets these requirements with the lowest operational overhead? (Choose two.)
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Correct answer: A, D
The correct answers are A and D.An AWS Glue trigger is a feature that lets you handle scheduled job execution entirely within the Glue service, resulting in lower operational overhead than implementing your own scheduling with Lambda (option C).
In addition, by using a Glue connection, you can securely and easily manage connection information between data sources and data stores such as RDS and Redshift, without having to implement additional API-call code.
DataBrew (B) is a no-code data preparation tool that is not needed for this requirement, and the Redshift Data API (E) adds implementation effort compared with using a Glue connection.
AWS Glue: Scheduling job runs with triggers (AWS official documentation)
Q6AWS Certified Data Engineer Associate
Q6. A media company uses an Amazon Redshift cluster running on RA3 nodes.
The company wants to scale read and write capacity on demand.
A data engineer needs to identify a solution that enables Concurrency Scaling.
Which solution meets this requirement?
Show answer
Correct answer: B. Enable concurrency scaling at the workload management (WLM) queue level of the Redshift cluster.
The correct answer is B.On a provisioned Redshift cluster, concurrency scaling must be enabled on a per-WLM-queue basis, which allows work to be distributed to temporary additional clusters when query load increases.
Option A is incorrect because the setup in this case uses a provisioned cluster rather than Redshift Serverless.
It is not an item that is fixed at cluster creation time as in option C; it is configured individually per WLM queue.
The usage quota in option D is a cost-management mechanism and is unrelated to enabling concurrency scaling.
Amazon Redshift: About concurrency scaling (AWS official documentation)
Q7AWS Certified Data Engineer Associate
Q7. A data engineer at a logistics company needs to orchestrate a series of Amazon Athena queries that run every day.
Each query can take 15 minutes or more to run.
Which combination of steps meets these requirements most cost-effectively? (Choose two.)
Show answer
Correct answer: A, B
The correct answers are A and B.Because the maximum execution time of a Lambda function is 15 minutes, you cannot wait within Lambda for an Athena query that may exceed 15 minutes to complete.
Therefore, by using a Step Functions Wait state and periodically checking the status with get_query_execution, you can orchestrate cost-effectively while avoiding Lambda’s timeout constraint.
Using Glue Python shell jobs (C, D) or MWAA (E) for continuous running and monitoring incurs additional execution-time charges compared with Step Functions and is less cost-efficient.
AWS Step Functions: Service integration with Amazon Athena (AWS official documentation)
Q8AWS Certified Data Engineer Associate
Q8. A gaming development company is planning to migrate its on-premises workloads to AWS.
The company wants to reduce overall operational overhead.
It also wants to consider serverless options.
The current workloads use Apache Pig, Apache Oozie, Apache Spark, Apache HBase, and Apache Flink.
The on-premises workloads process petabytes of data in seconds.
The company must maintain the same or better performance after migrating to AWS.
Which extract, transform, and load (ETL) service meets these requirements?
Show answer
Correct answer: B. Amazon EMR
The correct answer is B.Because Amazon EMR natively supports a wide variety of open-source frameworks such as Apache Spark, Pig, Oozie, HBase, and Flink and can process large-scale data at high speed, you can migrate while maintaining the compatibility and performance of existing workloads.
AWS Glue (A) supports Apache Spark-based ETL but does not support Oozie, HBase, Flink, and others, so it does not meet the requirements.
AWS Lambda (C) has constraints on execution time and memory and is unsuitable for large-scale data processing.
Amazon Redshift (D) is a data warehouse service and is not suited as an ETL platform.
Note that near-serverless options such as EMR Serverless, provided within the EMR framework, also exist.
What is Amazon EMR (AWS official documentation)
Q9AWS Certified Data Engineer Associate
Q9. A data engineer at a health insurance company needs to ingest datasets into an Amazon S3 data lake using AWS services.
When profiling a dataset, the engineer found that it contains personally identifiable information (PII).
The data engineer must implement a solution that profiles the dataset and obfuscates the PII.
Which solution meets this requirement with the lowest operational overhead?
Show answer
Correct answer: B. Use the AWS Glue Studio Detect PII transform to identify and obfuscate the PII. Orchestrate the pipeline that ingests the data into the S3 data lake with an AWS Step Functions state machine.
The correct answer is B.Because the AWS Glue Studio Detect PII transform provides not only PII detection but also obfuscation capabilities such as masking and redaction out of the box, it can perform identification and obfuscation together without additional code.
By contrast, the AWS Glue Data Quality in option C is a rule-based feature for validating the integrity and accuracy of data and is not a feature for obfuscating data, so it is incorrect.
Kinesis Firehose plus Lambda (A) and DynamoDB plus Lambda (D) require developing and maintaining custom code, which results in higher operational overhead.
AWS Glue: Detecting and processing sensitive data (AWS official documentation)
Q10AWS Certified Data Engineer Associate
Q10. A logistics company maintains multiple extract, transform, and load (ETL) workflows that ingest data from core databases into an Amazon S3-based data lake.
These ETL workflows use AWS Glue and Amazon EMR for data processing.
The company wants to improve its existing architecture, provide automated orchestration, and minimize manual effort.
Which solution meets these requirements with the lowest operational overhead?
Show answer
Correct answer: B. AWS Step Functions tasks
The correct answer is B.AWS Step Functions natively supports service integrations for both AWS Glue jobs and Amazon EMR jobs, so you can automate workflows serverlessly without building and maintaining a dedicated execution environment.
AWS Glue workflows (A) are limited to coordinating jobs within Glue, and incorporating EMR jobs requires additional workarounds.
Implementing your own orchestration with AWS Lambda (C) increases maintenance costs.
Amazon MWAA (D) enables flexible orchestration, but the cost of building and operating an Airflow environment is higher than Step Functions.
AWS Step Functions: Service integration with Amazon EMR (AWS official documentation)