Real-Time Analytics Platform for Gig Worker Performance Insights

In the fast-paced gig economy, platforms need to quickly adapt to changing worker dynamics and customer demands. Our startup aims to create a real-time analytics solution that empowers gig platforms with actionable insights on worker performance and customer satisfaction. The project requires building a scalable data engineering pipeline using technologies like Apache Kafka for event streaming, Apache Spark for real-time processing, and Snowflake or BigQuery for data warehousing. By integrating data from multiple touchpoints, including app usage data, customer feedback, and transaction records, the platform will provide a comprehensive view of performance metrics such as task completion rates, worker reliability scores, and satisfaction indexes. The solution will also incorporate data observability features using tools like Airflow and dbt to ensure data accuracy and pipeline reliability. This project is crucial for our clients to maintain competitive advantage and improve gig worker retention by offering insights into worker engagement and areas for improvement.