Real-Time Data Pipeline Optimization for Enhanced Warehouse Operations

As a rapidly growing company in the Warehousing & Distribution industry, we face challenges with our existing data pipeline's ability to process and analyze data in real-time. This limitation impacts our ability to make timely decisions critical for maintaining efficiency and competitiveness. We require a skilled data engineer to redesign and optimize our data architecture. The ideal solution will leverage Apache Kafka for event streaming, Spark for real-time analytics, and integrate tools like Airflow and dbt for workflow management and transformations. We are keen to move towards a data mesh architecture, ensuring data observability and seamless integration with platforms such as Snowflake or BigQuery for storage and analysis. The successful implementation will enhance our ability to predict demand, optimize inventory levels, and improve supply chain efficiency, ultimately leading to increased customer satisfaction and reduced operational costs.