Healthcare Data Pipeline Optimization for Real-time Analytics

As a leading player in the healthcare industry, we are committed to utilizing data to improve patient care and operational efficiency. We are embarking on a project to optimize our data engineering pipeline to support real-time analytics capabilities. Currently, our data processing strategies face latency issues that hinder timely decision-making. The project will involve the integration of Apache Kafka for event streaming, Spark for fast data processing, and an orchestration tool like Airflow to manage workflows efficiently. Additionally, we'll use dbt for transforming raw data in Snowflake or BigQuery, depending on compatibility and scalability needs. The freelancer will work closely with our data science and IT teams to ensure the new pipeline supports robust data observability and integrates seamlessly into our existing MLOps framework. This optimization is critical for delivering timely insights into patient care metrics and operational performance, ultimately enhancing our service delivery.