Real-Time Inventory Optimization and Forecasting System for Grocery & Supermarkets

As a rapidly growing company in the grocery and supermarkets industry, we face challenges in efficiently managing inventory and predicting demand to minimize operational costs and enhance customer satisfaction. We are seeking an experienced data engineering team to create a real-time inventory optimization and forecasting system. The project will involve setting up a robust data pipeline using Apache Kafka and Spark, enabling real-time data processing and analysis. Integration with Snowflake or BigQuery will be necessary for scalable storage and complex query handling. We aim to employ MLOps practices for model deployment and monitoring, ensuring our forecasting models remain accurate and relevant. The project will also focus on data observability to maintain data quality and reliability, and use of technologies like dbt and Airflow for data transformation and workflow orchestration. This system will allow us to dynamically adjust our inventory levels based on live sales data and market trends, significantly reducing waste and stockouts.