Welcome to Fever! As the world's premier technology platform for culture and live entertainment, we are on a mission to make cultural experiences accessible to everyone. Our innovative technology and data-centric approach are transforming the way individuals engage with live entertainment. Each month, our platform captivates over 300 million users across more than 40 countries, enabling them to discover remarkable events while empowering creators with the insights and technology they need to innovate and expand their reach. Our achievements include collaborations with industry titans such as Netflix, F.C. Barcelona, and Primavera Sound, along with several prestigious awards and support from top global investors! Exciting, isn't it? To continue our journey, we are seeking passionate individuals with a proactive mindset ready to help us redefine the future of entertainment!Now, let’s dive into the specifics of this role and how you can contribute to Fever's mission.About the RoleAt Fever, we are constructing a federated data organization that balances centralization where it matters and autonomy that drives value. Our teams utilize advanced data platforms like Snowflake, DBT, Airflow, DataHub, and Metabase. Moreover, we are developing proprietary technologies to deliver high-quality data products across diverse business sectors.As a Senior Analytics Engineer, you will serve as a crucial link between data engineering and business analytics, enabling our stakeholders to make informed decisions based on reliable, well-structured, and easily accessible datasets.What You’ll DoDesign, build, and maintain robust data models (DBT, SQL) that convert raw data into clean, trustworthy datasets for self-service and reporting.Collaborate with the data engineering team to define and validate business-critical metrics (revenue, engagement, marketing performance, B2B KPIs, etc.).Engage with business squads (B2B, Marketing, CRM, Product) to identify their requirements and transform them into reusable data assets.Ensure data quality and consistency by working closely with the data engineering team on testing frameworks, observability, and governance.Enable self-service analytics by empowering stakeholders to access and analyze data independently.
Feb 23, 2026
