Real-Time Data Pipeline Development for Commercial Real Estate Insights

In the competitive landscape of commercial real estate, timely insights can dramatically impact decision-making and investment strategies. Our startup is focused on empowering property managers and investors with real-time data analytics to enhance operational efficiencies and investment returns. We are looking to develop a robust data pipeline that integrates various data sources, including market trends, tenant behaviors, and property performance metrics. The project will involve setting up an event streaming architecture using Apache Kafka for real-time data ingestion, while leveraging Spark for scalable data processing. Airflow will be used for orchestrating data workflows, and dbt will facilitate transformation processes to ensure data quality and accessibility. The processed data will be stored in Snowflake or BigQuery for scalable querying and analytics. Additionally, we aim to implement MLOps principles to enable predictive analytics capabilities. This project is critical for delivering timely insights to our clients, and we seek a freelancer who can deliver within a rapid timeline of 4-6 weeks.