A data engineer must implement Amazon Redshift Serverless as a data warehouse for a company.

Amazon Aurora zero-ETL integration with Amazon Redshift Serverless is designed specifically to provide near real-time analytics on transactional data with minimal operational overhead. This integration continuously replicates changes from Aurora MySQL databases into Redshift Serverless without requiring data pipelines, replication tasks, or infrastructure management.

Because the requirement emphasizes near real-time latency and minimal management, zero-ETL integration is the optimal choice. It eliminates the need to configure and monitor AWS DMS tasks, manage Glue jobs, or build and scale Lambda-based ingestion logic. Schema changes, data synchronization, and replication are handled automatically by AWS.

AWS DMS Serverless, while managed, still requires task configuration and monitoring and typically introduces more latency than zero-ETL integrations. AWS Glue jobs and Lambda functions require custom code, scheduling, and error handling, increasing both complexity and maintenance effort.

Therefore, setting up Aurora zero-ETL integration with Amazon Redshift Serverless best satisfies the requirements and aligns with AWS best practices for modern analytics architectures.