Real-Time Data Pipeline Enhancement for Optimized Patient Care in Telemedicine

As a rapidly growing telemedicine provider, we aim to optimize our data management processes to support real-time decision-making and enhance patient care. We're seeking a data engineering expert to develop and implement a scalable, real-time data pipeline leveraging technologies such as Apache Kafka, Spark, and Snowflake. The project involves designing a system architecture that supports data mesh principles, allowing decentralized data management aligned with individual departments' needs. Key objectives include integrating event streaming for real-time insights, implementing data observability procedures to ensure data integrity and reliability, and facilitating predictive analytics through MLOps practices. The project will require close collaboration with our data science team to ensure seamless integration of machine learning models and with our IT department to align with existing data governance frameworks.