Real-Time Data Pipeline Development for Enhanced Property Management Insights

As a rapidly growing PropTech company, we aim to elevate our property management platform by transitioning to a real-time data processing model. Currently, our insights are delayed due to batch processing, which hampers our ability to make informed, timely decisions. We are seeking a skilled data engineer to design, implement, and optimize a real-time data pipeline leveraging technologies such as Apache Kafka, Spark, and Airflow. The project involves integrating diverse data sources, enabling real-time data ingestion, and providing the foundation for predictive analytics using tools such as dbt and Snowflake. This will empower property managers with instant data-driven insights, enhancing operational efficiency and tenant satisfaction. The ideal candidate will have experience in real-time data streaming, data orchestration, and cloud data warehousing technologies, ensuring scalability and reliability of the pipeline. The ultimate goal is to transform our data infrastructure to support a data mesh architecture that promotes data accessibility and governed self-service analytics across our teams.