50 AWS Certified Data Engineer - Associate Practice Questions: Question Bank 2025

A data engineering team stores raw and curated datasets in Amazon S3. They want to ensure that no one can delete or overwrite objects in the curated prefix for 30 days, even if an IAM principal has s3:DeleteObject permissions. Which solution best meets this requirement?

A company wants to ingest clickstream events from a web application with minimal operational overhead. Events must be available for near-real-time analytics in Amazon Redshift, and the pipeline should scale automatically with traffic spikes. Which approach is most appropriate?

An analytics team uses Amazon Athena to query data in Amazon S3. They notice queries are slow and scan large amounts of data. The dataset is partitioned by day, but most queries filter by customer_id. What is the MOST effective way to reduce scanned data for these queries while keeping the solution serverless?

A team runs an AWS Glue ETL job that intermittently fails with "No space left on device" errors during large shuffles. What is the best first change to improve job reliability without changing the business logic?

A company uses Amazon Redshift for analytics and wants to restrict analysts to see only the rows for their assigned region across multiple tables, without duplicating tables or creating separate clusters. Which feature should the company use?

A data platform uses AWS Lake Formation with an S3 data lake. The team wants to grant a new data analyst permissions to query specific tables with Amazon Athena, but the analyst should not receive direct Amazon S3 permissions to the underlying buckets. What is the recommended approach?

A streaming pipeline uses Amazon Kinesis Data Streams. A consumer application is falling behind and reports increasing iterator age. The team wants to scale reads without modifying producers and while keeping ordering within each shard. What should they do?

A team uses Amazon S3 as a data lake and AWS Glue Data Catalog for metadata. They need to keep table partitions up to date as new hourly folders arrive, with the least operational overhead. What is the best solution?

A company maintains a curated S3 data lake accessed by Athena and Amazon EMR. They need to implement ACID transactions, schema evolution, and reliable upserts on large partitioned datasets. They also want the table format to be interoperable across engines. Which solution best meets these requirements?

A data engineering team is building a centralized analytics account. Source accounts in the organization must deliver sensitive datasets to a shared Amazon S3 bucket. The security team requires that objects are encrypted with a customer managed key and that the source accounts cannot decrypt data after it is delivered. Which design meets these requirements?

A data engineering team uses Amazon S3 as a data lake. They want to prevent accidental deletion or overwrites of raw data objects while still allowing new objects to be written. Which solution best meets this requirement?

A company must ensure that only approved AWS accounts within the organization can access a curated S3 bucket. The company wants to enforce this at the bucket level using an AWS-native governance control. What should the data engineer implement?

A team manages data ingestion with AWS Glue jobs that write Parquet files to Amazon S3. The team wants to automatically discover newly added partitions and make them available for querying in Amazon Athena with minimal operational effort. Which approach should they use?

A company uses Amazon Redshift for analytics. Data is loaded continuously into staging tables, and analysts query curated tables. The company wants to minimize lock contention and ensure consistent query performance during heavy loads. Which Redshift design is most appropriate?

A data platform uses AWS Lake Formation for governance. Users should be able to query only specific columns in a table and only rows where region = 'EU' using Athena. Which solution meets the requirement with the least operational overhead?

A company streams click events into Amazon Kinesis Data Streams. A consumer application occasionally falls behind due to downstream throttling and must reprocess records after it recovers. Which configuration will best support reprocessing without data loss?

A data engineer needs to run SQL transformations on data stored in Amazon S3 and write the results back to S3 in Parquet format. The workload is mostly ad hoc but should start quickly and require minimal infrastructure management. Which service is the best fit?

A pipeline runs an AWS Glue job nightly and then triggers several dependent steps. The team needs centralized orchestration, retries, and visibility into each step’s status without building custom polling logic. Which solution should the team use?

A company stores sensitive customer data in Amazon S3 and uses AWS Glue Data Catalog and Athena for queries. Security requires end-to-end encryption and the ability to audit which user accessed which dataset. Which solution best meets these requirements?

A data engineer must build a near-real-time ingestion solution from an on-premises database into Amazon S3 with exactly-once delivery semantics for downstream processing. The solution should handle schema evolution and provide a durable commit log. Which approach is most appropriate?

A company runs an hourly AWS Glue ETL job that reads from Amazon S3 and writes curated data back to S3 in Parquet format. The job frequently reruns for the same hour because of upstream delays, and the data engineering team must ensure duplicate output files are not created. What is the BEST approach to make the job idempotent?

A data engineer needs to allow Amazon Redshift to query data in an Amazon S3 data lake without loading it into Redshift storage. Which feature should the engineer use?

A team wants to be notified when an AWS Glue job fails and include the job name and run ID in the alert. Which solution is MOST appropriate?

A company streams clickstream events into Amazon Kinesis Data Streams. The producer occasionally retries and sends the same event multiple times. The company uses Amazon Kinesis Data Analytics for Apache Flink to compute unique sessions and must prevent double-counting. What should the data engineer do?

A data engineer is creating an AWS Lake Formation governed data lake on Amazon S3. Analysts should be able to query only specific columns that contain non-sensitive data from a table using Amazon Athena. Which Lake Formation capability should the engineer use to meet this requirement?

A company runs Apache Spark ETL jobs on Amazon EMR and writes output to an S3 data lake. The team needs table metadata and partitions to be discoverable and queryable by Amazon Athena and Amazon Redshift Spectrum with minimal operational overhead. Which solution should the data engineer implement?

A data pipeline uses AWS Glue to transform data and write it to an Amazon S3 curated zone. Data quality checks run after the write. When a quality check fails, the team must be able to identify exactly which input objects contributed to the bad output and who initiated the run. Which combination of AWS capabilities BEST supports this requirement?

A company stores semi-structured JSON in Amazon S3 and queries it with Amazon Athena. Queries have become slow and expensive because they scan large volumes of data. The data arrives continuously and contains a timestamp field. Which approach provides the MOST effective performance improvement with minimal query changes?

A company uses Amazon Redshift as its analytics warehouse. A security requirement states that analysts must not be able to see raw PII, but they should be able to join datasets using a consistent pseudonymous identifier. The solution must minimize changes to existing SQL queries. Which solution BEST meets these requirements?

An organization runs multiple AWS accounts and has several Amazon S3 data lake buckets registered in AWS Lake Formation. Different business units require isolation so that permissions are administered separately, but a central governance team must retain the ability to audit and enforce access policies across accounts. Which design BEST meets these requirements?

A data engineering team wants to ingest JSON events from thousands of mobile devices. Events can arrive out of order, and the team needs to replay the last 24 hours of data for backfills. Which AWS service is the best fit as the primary ingestion layer?

A team writes daily Parquet files to Amazon S3 in a data lake. Analysts complain that partition discovery is inconsistent and new partitions are not always visible to Athena queries. Which action is the MOST appropriate way to keep the table metadata current?

A data engineer needs to grant a data analyst read-only access to a specific AWS Glue Data Catalog database and its tables, without granting access to other databases. Which solution is the MOST appropriate?

A data pipeline uses AWS Glue jobs. The team wants to be alerted when a job run fails and automatically route the alert to an on-call email distribution list. Which solution meets this requirement with the LEAST operational effort?

A company uses Amazon Redshift for analytics. They frequently load data from Amazon S3 and notice slower performance due to many small files. What is the BEST approach to improve load performance?

A team stores curated datasets in Amazon S3 and queries them with Athena. They need to ensure analysts can only see rows for their business unit (row-level access control). Which solution is MOST appropriate?

A near-real-time pipeline reads records from Kinesis Data Streams and writes aggregates to DynamoDB. During traffic spikes, the consumer application falls behind and the iterator age increases. Which change is the MOST effective way to reduce lag without changing the producers?

A team uses AWS Glue ETL jobs to transform data in Amazon S3. They must ensure schema changes (new columns) do not silently break downstream Athena queries and that changes are tracked over time. Which approach is BEST?

A company runs an S3-based data lake with multiple producer accounts writing to a central bucket in a data platform account. The platform team must prevent producers from deleting or overwriting existing objects while still allowing them to add new data. Which solution BEST meets these requirements?

A team uses Amazon Redshift and needs to allow a partner to query only a subset of tables without copying data out of the cluster. The partner uses a separate AWS account. The solution must minimize ongoing maintenance and support fine-grained access control. Which approach is BEST?

A data engineering team needs to catalog Parquet files stored in Amazon S3 so analysts can query them using Amazon Athena. New partitions arrive daily under paths like s3://bucket/events/dt=YYYY-MM-DD/. The team wants the catalog to update automatically with minimal manual effort. Which solution should they use?

A company wants to encrypt all objects in an Amazon S3 bucket that stores curated datasets. They also want to ensure that no unencrypted objects can be uploaded, even if a user attempts to bypass defaults. Which approach best meets this requirement?

An organization is using AWS Lake Formation to manage access to tables registered in the AWS Glue Data Catalog. A new analyst should be able to query only specific columns that contain non-sensitive data. Which Lake Formation capability should be used?

A pipeline loads clickstream events into Amazon S3 and triggers an AWS Glue ETL job. The job intermittently fails with "OutOfMemoryError" when processing large partitions. The team wants a solution that reduces failures without changing business logic. What should they do?

A company uses Amazon Kinesis Data Streams to ingest IoT telemetry. Downstream consumers must be able to reprocess data from the last 24 hours after a bug fix. The current application cannot re-read old records because they have already expired. What change best meets the requirement?

A data team stores raw and curated datasets in Amazon S3. They want to run a daily process that finds objects older than 30 days in the raw prefix and transitions them to a lower-cost storage tier automatically. Which solution is the MOST operationally efficient?

A company runs analytics queries in Amazon Redshift. Users report that some queries are slow because they scan many blocks even when filtering on a timestamp column. The team wants to optimize for range filters on that timestamp with minimal changes to the application. Which action is most appropriate?

A company uses AWS Glue Data Catalog and Amazon Athena. They enforce governance with AWS Lake Formation. An engineer grants a user Lake Formation permissions to SELECT from a table, but the user still receives an "Access denied" error when querying in Athena. Which additional requirement is MOST likely missing?

A company needs to ingest change data capture (CDC) from an on-premises PostgreSQL database into an Amazon S3 data lake with minimal latency. They want schema changes to be handled gracefully and prefer a managed service to capture ongoing changes. Which solution best fits?

A company must share a governed dataset stored in Amazon S3 with another AWS account. The provider wants to control access using Lake Formation and ensure consumers can query the data in their own account without copying it. Which approach should they use?