Welcome to Fever! We are the leading tech platform globally for culture and live entertainment.Our mission is simple: to democratize access to culture and entertainment. Through our innovative technology and data-centric approach, we are transforming how people experience live entertainment. Each month, we inspire over 300 million individuals across more than 40 countries, enabling event creators with our data and technology to innovate and connect with new audiences.Our achievements include collaborations with prominent industry giants such as Netflix, F.C. Barcelona, and Primavera Sound, along with internationally acclaimed experiences, all supported by top-tier global investors. Quite impressive, isn’t it?To fulfill our mission, we seek ambitious individuals with a practical mindset who are excited to help shape the future of entertainment!Are you ready to join us on this journey?Let’s delve into this role and discover how you can contribute to Fever’s mission.About the RoleAt Fever, we are developing a federated data organization that harmonizes centralization where necessary and autonomy where it adds value. Our teams utilize modern data platforms (Snowflake, DBT, Airflow, DataHub, Metabase, etc.), and we are also creating our own technology to provide high-quality data products across various business sectors.As a Business Intelligence Engineer, you will serve as a crucial link between data engineering and business analytics, ensuring our stakeholders have access to reliable, well-structured, and easily discoverable datasets.Your ResponsibilitiesDesign, develop, and sustain data models (DBT, SQL) that convert raw data into clean, reliable datasets for self-service and reporting purposes.Collaborate with the data engineering team to define and validate essential business metrics (revenue, engagement, marketing performance, B2B KPIs, etc.).Engage with business squads (B2B, Marketing, CRM, Product) to comprehend their requirements and translate them into reusable data assets.Ensure data quality and consistency by partnering with the data engineering team on testing frameworks, observability, and governance.Facilitate self-service analytics by empowering stakeholders to access and analyze data autonomously.
Feb 24, 2026