Real-time Data Pipeline Optimization for Enhanced Telemedicine Services

As a growing player in the telemedicine industry, we recognize the critical need for timely and accurate data to support our healthcare professionals in delivering superior telehealth services. We are seeking an experienced data engineer to enhance our data infrastructure by implementing a real-time data pipeline architecture. The project will focus on adopting a data mesh strategy, which involves decentralizing data ownership and improving accessibility across different departments. You will work with technologies such as Apache Kafka for event streaming, Apache Spark for large-scale data processing, and tools like Airflow and dbt to orchestrate and transform data workflows. Our current systems require optimization to handle increased patient data volume, ensure real-time availability, and support the integration of MLOps practices for predictive analytics. This project is pivotal in reducing latency, improving data accuracy, and enabling faster decision-making processes within our organization.