Scalable Data Engineering Platform for Real-Time Analytics in Organic & Natural Foods

As a leader in the Organic & Natural Foods industry, we are committed to delivering high-quality, sustainable products to our consumers. However, we face challenges in efficiently managing our vast data pipeline, which is crucial for driving decisions around supply chain optimization, inventory management, and customer engagement. We require a robust data engineering platform that supports real-time analytics, enabling us to respond swiftly to market demands and consumer preferences. The project involves architecting a scalable solution using technologies such as Apache Kafka for event streaming, Spark for distributed data processing, Airflow for workflow orchestration, and Snowflake or BigQuery for data warehousing. Integration with MLOps tools will further allow us to implement predictive analytics models, enhancing our decision-making capabilities. By the end of this project, we aim to achieve a data mesh architecture that promotes data observability and decentralization, empowering different departments to act upon data-driven insights independently.