Real-time Nutritional Data Pipeline Implementation

As a leading enterprise in the Nutrition & Dietetics industry, we aim to revolutionize how we handle and analyze nutritional data. With an increasing demand for personalized dietary solutions and efficient supply chain management, we need a robust data engineering solution to process real-time data streams efficiently. The project involves designing and implementing a real-time data pipeline utilizing technologies such as Apache Kafka for event streaming, Spark for large-scale data processing, and Airflow for workflow orchestration. We aim to integrate these with our existing data warehousing solutions, like Snowflake or BigQuery, to ensure seamless data flow and accessibility. The new architecture will also leverage data mesh principles, allowing decentralized ownership of data domains while ensuring data availability and observability across the organization. This initiative will not only support our analytics team in delivering timely insights but also position us at the forefront of innovation in personalized nutrition.