Real-time Data Pipeline Optimization for Specialty Foods Supply Chain

As a leading enterprise in the specialty foods sector, we are committed to delivering high-quality products to our customers efficiently and sustainably. Our current supply chain operations rely on data pipelines that are not fully optimized for real-time analytics, which hampers our ability to make informed decisions quickly. This project aims to redesign and implement advanced data pipelines using technologies such as Apache Kafka, Spark, Airflow, and dbt. The goal is to create a cohesive data mesh that supports real-time event streaming and analytics. By integrating with platforms like Snowflake and BigQuery, we aim to enhance data observability and apply MLOps principles for continuous improvement. The successful execution of this project will allow us to maintain our competitive edge by optimizing inventory levels, reducing waste, and improving delivery times. The freelancer will collaborate closely with our internal data and IT teams to ensure seamless integration and stakeholder alignment.