Real-Time Fan Engagement Analytics Platform for Sports Events

As a budding startup in the Sports & Recreation industry, we recognize the critical role of fan engagement in enhancing the overall sporting experience. With the rise of digital interaction during live sports events, we aim to develop a Real-Time Fan Engagement Analytics Platform. This platform will collect and process data from various sources, including social media mentions, in-app interactions, and live feedback, to provide real-time insights into fan sentiment, engagement levels, and emerging trends. We are seeking a freelancer with expertise in data engineering to design and implement a data pipeline utilizing technologies such as Apache Kafka for event streaming, Spark for data processing, and Snowflake for data storage. The project involves setting up a robust infrastructure to handle high volumes of data with low latency, enabling sports organizers and teams to make informed engagement strategies on-the-fly. Additionally, the implementation of MLOps practices will ensure the scalability and reliability of the machine learning models integrated into the platform for predictive analytics.