During May 2025, Kh implemented tumbling window support for event data models in the aws-powertools/powertools-lambda-python and aws-powertools/powertools-lambda-typescript repositories. This work introduced time-based aggregation capabilities for Kinesis and DynamoDB streams, enabling Lambda functions to process and analyze data in discrete windows. Kh updated data classes and schema definitions in both Python and TypeScript, ensuring consistent event parsing and reliable windowed analytics. The implementation included comprehensive tests to validate time-based aggregations and enhanced the overall data modeling for streaming workloads. This focused, foundational work deepened the event processing capabilities and improved schema validation for AWS Lambda-based streaming applications.