Real-Time Data Pipeline Enhancement for Renewable Energy Grid Optimization

As a scale-up in the renewable energy sector, we are committed to optimizing our energy distribution network to achieve maximum efficiency. Our current data infrastructure needs an upgrade to support real-time analytics and improve decision-making processes. We aim to build an advanced data pipeline that seamlessly integrates data mesh principles for efficient data management across departments. This project will involve setting up a real-time event streaming platform using Apache Kafka, orchestrating data flows with Apache Airflow, and processing data using Spark. Additionally, we will implement data observability practices to ensure data quality and reliability. By leveraging cloud data warehouses like Snowflake or BigQuery, we aim to achieve a unified data view that supports our machine learning models for predictive maintenance and energy load forecasting. The successful execution of this project will enable us to respond faster to grid demands, reduce energy waste, and improve overall operational efficiency.