Real-time Data Pipeline Implementation for Optimized Food Processing

As a growing SME in the food processing industry, we recognize the need to enhance our operational efficiency by utilizing real-time data analytics. We are looking for a skilled data engineer to design and implement a real-time data pipeline that will allow us to monitor and optimize our production processes effectively. This project will involve setting up an event-driven architecture using Apache Kafka to manage data streams from various production units. Spark will be used for real-time data processing and analytics, enabling us to identify bottlenecks and inefficiencies quickly. The data pipeline will also incorporate Apache Airflow for scheduling and orchestration, while dbt will ensure data quality and consistency. For data storage and querying, we plan to use Snowflake or BigQuery, providing us with scalable and flexible data warehousing capabilities. The successful implementation of this project is expected to lead to significant improvements in production efficiency, reduced waste, and an overall increase in profitability.