Real-time Analytics Pipeline for Enhanced Patient Care in Telemedicine

As a rapidly growing player in the telemedicine industry, we recognize the need to harness the power of data to enhance patient outcomes and streamline our services. We are seeking a skilled data engineer to develop a real-time analytics pipeline that can process and analyze data from various sources, such as patient interactions, clinical data, and operational metrics. The solution will utilize technologies like Apache Kafka for event streaming, Spark for real-time data processing, and Snowflake for data warehousing. The objective is to create a data architecture that supports real-time decision-making and operational insights. The project will involve setting up a data mesh architecture to ensure data observability and scalability, integrating MLOps practices to support machine learning models, and ensuring data quality and governance. The successful implementation of this pipeline will empower our medical and operational teams to make informed decisions quickly, ultimately improving patient care and operational efficiency.