Senior Analytics Engineer (Data Modeling & BI)

Hey there! We’re Fever , the world’s leading tech platform for culture and live entertainment.

Our mission? To democratize access to culture and entertainment. With our proprietary cutting-edge technology and data-driven approach, we’re revolutionizing the way people engage with live entertainment.

Every month, our platform inspires over 300 million people in +55 countries (and counting) to discover unforgettable experiences while also empowering event creators with our data and technology, helping them scale, innovate, and enhance their events to reach new audiences.

Our results? We’ve teamed up with major industry leaders like Netflix, F.C. Barcelona, and Primavera Sound, presented international award-winning experiences, and are backed by several leading global investors! Impressive, right?

To achieve our mission, we are looking for bar-raisers with a hands-on mindset who are eager to help shape the future of entertainment!

Ready to be part of the experience?

Now, let’s discuss this role and what you will do to help achieve Fever’s mission.

At Fever, we are building a federated data organization that combines centralization where it’s essential and autonomy where it creates value. Our teams leverage modern data platforms (Snowflake, DBT, Airflow, DataHub, Metabase, etc.). At the same time, we are developing our own technology to deliver high-quality data products across multiple business domains.

As a Senior Analytics Engineer, you’ll be the bridge between data engineering and business analytics, ensuring that our stakeholders can make decisions on reliable, well-modeled, and discoverable datasets.

This role can be based in Barcelona or Madrid.

* Design, build, and maintain data models (DBT, SQL) that transform raw data into clean, trusted datasets for self-service and reporting. * Collaborate with the data engineering team to define and certify business-critical metrics (revenue, engagement, marketing performance, B2B KPIs, etc.). * Work with business squads (B2B, Marketing, CRM, Product) to understand their needs and turn them into reusable data assets. * Ensure data quality and consistency, partnering with the data engineering team on testing frameworks, observability, and governance. * Support self-service analytics by enabling stakeholders to explore data confidently by leveraging existing viz and BI tools or driving custom developments to let the data tell a complete story. * Contribute to Airflow pipelines in Python, supporting automation and orchestration needs. * Contribute to our data mesh vision, creating domain-owned datasets while following platform and engineering guidelines. * Leverage Agentic AI, Claude Code, and other advanced AI tools in your day-to-day workflow to accelerate development cycles, boost efficiency, and maximize your overall impact.