Developed an event-driven, serverless data processing pipeline for the CDCgov/dibbs-ecr-refiner repository, focusing on automating EICR and RR data refinement. Leveraging AWS Lambda and S3, the solution ingested base64-encoded payloads from S3 events, decoded the data, and generated refined XML documents, which were then written back to S3 for downstream use. The implementation included updating the Dockerfile and introducing a Lambda-specific requirements file to streamline deployment and dependency management. Using Python and Docker, this work established a scalable, automated flow that reduces manual intervention in XML processing and supports efficient, cloud-native data handling for healthcare data pipelines.