Which combination of steps should a solutions architect take to meet these requirements?

Explanations:

Amazon Redshift is designed for data warehousing and is not optimized for hierarchical data storage and high-latency responses. While unloading data to Amazon S3 can be useful for archiving or analytics, it does not directly address the needs for minimum-latency queries or sensitive data protection.

Amazon DynamoDB is a NoSQL database that allows for efficient hierarchical data storage with low-latency responses, making it suitable for high-traffic queries. Exporting the data to Amazon S3 monthly can help with backup or further analysis if required.

While Amazon Macie can help identify sensitive data, it does not directly facilitate the storage or querying of employee data or integrate with EventBridge for monthly events effectively without a specific trigger or condition. This option does not address the high-traffic query requirement.

Amazon Athena can analyze data stored in Amazon S3 but does not address the requirement for hierarchical storage or the need for low-latency responses to high-traffic queries. Additionally, it does not help in sending notifications regarding sensitive financial information.

Amazon Macie can identify sensitive financial data in employee records. Integrating it with Amazon EventBridge allows for the configuration of events based on Macie’s findings, which can then trigger notifications through Amazon SNS, thus meeting the requirement for monthly notifications.