Real-Time Data Analytics Pipeline for Water Quality Monitoring

In the evolving landscape of water treatment, timely and accurate data analysis is paramount. Our company, an SME with a focus on innovation, faces challenges in efficiently monitoring water quality across multiple locations. We aim to implement a state-of-the-art data engineering solution that leverages Apache Kafka for real-time data ingestion and Spark for processing large datasets. The pipeline will integrate with Airflow for orchestrating workflows, dbt for data transformation, and Snowflake or BigQuery for scalable data storage and querying. The project will also incorporate data observability practices, enabling proactive monitoring and maintenance of data quality. By implementing this solution, our company seeks to enhance its operational capabilities and ensure compliance with regulatory standards while reducing costs and increasing responsiveness to potential issues. The project is expected to be completed within 12-16 weeks and requires expertise in modern data engineering tools and practices.