AWS Certified Data Engineer - Associate Practice Exam 2025: Latest Questions

A company receives CSV files every hour in an Amazon S3 landing bucket. They want to automatically convert the files to Apache Parquet, partition by ingest_date, and store the results in a curated S3 bucket for Athena queries. The solution should require minimal custom code. What should they use?

An analytics team uses Amazon Athena to query data in Amazon S3. They want a centralized place to store table definitions and schemas so multiple accounts can reuse them consistently. Which AWS service provides this capability?

A team runs daily ETL workflows orchestrated by AWS Step Functions. They need to be alerted when any workflow execution fails and want to route notifications to an email distribution list. What is the MOST appropriate approach?

A security team wants to enforce encryption at rest for objects stored in an Amazon S3 bucket that contains curated analytics data. They also want to control key usage and rotation. Which solution best meets these requirements?

A company ingests clickstream events into an Amazon Kinesis Data Stream. They must deliver the raw events to Amazon S3 with near-real-time delivery, buffer and batch records efficiently, and optionally convert to Parquet. Which solution requires the LEAST operational effort?

A data platform uses Amazon Redshift for analytics. Query performance has degraded because certain fact tables are not evenly distributed across nodes, causing data skew and excessive network redistribution during joins. Which action is MOST likely to improve performance?

An AWS Glue job that writes partitioned Parquet data to Amazon S3 is succeeding, but queries in Amazon Athena are not returning newly ingested partitions. The team confirms the data files exist in the expected partition prefixes. What is the MOST likely fix?

A company wants to allow analysts to query sensitive datasets in Amazon S3 with Amazon Athena. They must restrict access so users can only see specific columns (for example, mask PII) and only rows for their business unit. The solution should be centrally managed and auditable. What should they use?

A company maintains a data lake in Amazon S3 with thousands of objects created daily. They want to ensure all new objects are tagged with a data-classification tag and encrypted with SSE-KMS. Noncompliant uploads must be automatically denied at write time. Which approach best meets these requirements?

A data engineering team needs to implement an upsert (insert/update) pipeline into an Amazon S3 data lake table while maintaining ACID transactions, supporting time travel, and enabling concurrent reads and writes from multiple jobs. They want the table to be queryable by multiple AWS analytics engines. Which solution is MOST appropriate?

A data engineering team stores curated datasets in Amazon S3. Analysts in a separate AWS account must be able to query these datasets using Amazon Athena, but the S3 objects must not be publicly accessible. Which approach meets the requirement with the LEAST operational overhead?

A company needs to stream clickstream events from an application to Amazon S3 for analytics. Events must be delivered within minutes and partitioned by event time (for example, year/month/day/hour) to optimize Athena queries. The solution must require minimal custom code. Which solution should a data engineer choose?

A data engineer is troubleshooting an AWS Glue ETL job that reads from Amazon S3 and writes Parquet output back to S3. The job frequently fails with OutOfMemory errors. The input contains a small number of very large files. Which change is MOST likely to resolve the failures without changing the output format?

A company uses Amazon Redshift for analytics. They need to give a BI team read-only access to a subset of rows in a table based on the user's region, without creating separate tables per region. Which feature should the data engineer use?

A team runs multiple Amazon EMR clusters for batch processing. They want to store and reuse common Spark and Hive configurations and bootstrap actions across clusters, and they want to minimize configuration drift. Which solution is MOST appropriate?

A company ingests CSV files into an Amazon S3 data lake. Some files have a new optional column added over time. Downstream consumers query the data using Athena and expect the newest schema while still being able to query historical data. Which approach is BEST?

A company stores sensitive customer data in Amazon S3 and uses AWS Glue and Athena for processing and querying. The security team requires that the data be encrypted with customer-managed keys and that only specific roles can use those keys. Which solution meets these requirements?

A data platform uses Amazon S3 as a data lake and AWS Glue Data Catalog for table definitions. A new governance requirement states that all datasets must have mandatory business metadata fields (for example, data owner, sensitivity classification) and that missing metadata must be detected. Which AWS service is BEST suited to manage and enforce this metadata governance requirement?

An analytics team uses Amazon Redshift. Queries that scan large tables are slowing down short, high-priority dashboard queries. The team wants to ensure consistent performance for dashboards without adding new clusters. Which action should a data engineer take?

A company runs near-real-time fraud detection using Amazon Kinesis Data Streams. Consumers occasionally fail and fall behind. The company must be able to reprocess data from up to 14 days in the past, but they want to minimize the cost and operational impact during normal processing. Which solution BEST meets these requirements?

A data engineer runs a daily AWS Glue job that reads new objects from an S3 prefix and writes curated Parquet files back to S3. Some days, upstream systems re-upload the same files, causing duplicates in the curated dataset. The data engineer needs to make the pipeline idempotent with minimal code changes. What should the data engineer do?

A company has an Amazon Redshift cluster with a schema used by analysts. The company wants to prevent analysts from seeing PII columns (for example, social security number) while allowing them to query non-PII columns in the same tables. The solution must not require copying data into separate tables. Which approach should the data engineer use?

An organization uses AWS Lake Formation to govern access to an S3 data lake registered in the AWS Glue Data Catalog. A new IAM role is granted Lake Formation SELECT permissions on a database and tables, but queries from Amazon Athena fail with an access denied error to the underlying S3 location. What is the most likely cause?

A streaming pipeline reads events from Amazon Kinesis Data Streams using Amazon Kinesis Data Analytics for Apache Flink and writes aggregates to Amazon S3. After a redeploy of the Flink application, the team notices missing aggregates for a brief time window. The team needs to reduce the chance of gaps and ensure state is recovered across restarts. What should the data engineer do?

A company uses Amazon DynamoDB to store IoT device telemetry as items keyed by deviceId with a sort key of timestamp. The table experiences sudden spikes and is throttling reads during incident investigations when analysts run ad hoc queries for large time ranges. The company needs to reduce throttling risk while keeping costs predictable. Which solution is recommended?