Real-time Listener Analytics Platform for Podcast & Radio Startup

As a Podcast & Radio startup, we are looking to implement a robust real-time analytics platform to gain deeper insights into listener engagement and behavior. The project focuses on building a scalable architecture that can process streaming data efficiently. We need a data engineering solution that utilizes technologies such as Apache Kafka for event streaming, Spark for processing, and Snowflake or BigQuery for data warehousing. The platform should enable us to analyze listener data in real-time, track metrics such as session duration, skip rates, and popular content segments, and provide dashboards for easy interpretation of data by non-technical stakeholders. By deploying Airflow for workflow orchestration and dbt for data transformation, we aim to ensure seamless data pipeline management. This project is critical for optimizing our content strategy, enhancing user experience, and refining our monetization efforts through targeted advertising. The chosen freelancer will work closely with our in-house team to implement this solution, emphasizing data observability and maintaining high standards of data quality.