Real-Time Health Data Pipeline Optimization for Enhanced Patient Outcomes

As a rapidly growing healthcare company, we are committed to improving patient outcomes through data-driven insights. Our current data infrastructure struggles with latency and data silos, impeding our ability to provide real-time analytics essential for critical healthcare decisions. We are looking for a data engineering expert to architect a real-time data pipeline. This project involves using Apache Kafka for event streaming, Spark for data processing, Airflow for workflow management, and dbt for data transformation. The pipeline will integrate with Snowflake for data warehousing and BigQuery for analytics, ensuring that our clinicians have access to up-to-date patient data. Key objectives include reducing latency, enhancing data observability, and improving data mesh architecture to enable decentralized data ownership. The success of this project will directly impact our ability to deliver timely health interventions and improve patient care, aligning with our mission to leverage technology for better healthcare outcomes.