Real-time Data Pipeline Optimization for Quality Control in Pharmaceutical Manufacturing

As a rapidly growing pharmaceutical manufacturing company, we are experiencing an expansion in production that requires a robust and scalable solution for real-time data processing and analytics. Our current systems are struggling to keep up with the increased data load, risking delays and potential compliance issues. We seek a data engineering expert to develop and optimize a real-time data pipeline using advanced technologies such as Apache Kafka for event streaming, Apache Spark for processing, and Snowflake for data warehousing. The project will involve implementing MLOps practices to integrate machine learning models for predictive analytics, ensuring swift identification of production anomalies. Additionally, data observability tools will be utilized to monitor data quality and lineage actively. The successful implementation of this project will not only streamline our quality control processes but also provide critical insights into production efficiency, reducing waste and ensuring compliance with pharmaceutical regulations.