Real-Time Environmental Impact Monitoring System with Advanced Data Engineering

Our scale-up company is seeking an advanced data engineering solution to enhance our environmental monitoring capabilities. The project involves developing a real-time data processing system to collect, process, and analyze environmental data from various sensors and IoT devices deployed across multiple sites. By leveraging technologies such as Apache Kafka for event streaming, Spark for data processing, and Snowflake for data warehousing, we aim to create a scalable and efficient data infrastructure. The system will also utilize Airflow for orchestrating data pipelines and dbt for data transformation, ensuring data accuracy and observability. The goal is to provide stakeholders with immediate access to critical environmental metrics, facilitating timely decision-making and reporting. This initiative is not only about compliance with environmental regulations but also about optimizing resource use and minimizing ecological footprints. The project will span 8-12 weeks, with a budget of $15,000 to $50,000, requiring expertise in the latest data engineering practices.