Senior Analytics Engineer (Data Modeling & BI)

Confirmed live in the last 24 hours

FeverUp

Madrid

On-site

Posted April 1, 2026

Job Description

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.

About the Role

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 an 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.

What You’ll Do

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.

What You Bring

Fluent in Spanish and English; you’ll communicate in Spanish with local teams and in English with global teams
A Bachelor’s, Master’s, or PhD in Computer Engineering, Data Engineering, Data Science, or a related field.
A collaborative mindset: comfortable working with both engineers and business stakeholders.
Strong communication skills, adaptable to a multidisciplinary, international, and fast-paced environment.
A keen interest in understanding a complex business landscape and to drive the company forward by providing the data to answer the most valuable questions
Strong experience with SQL and data modeling (star/snowflake schemas, data vault, or similar).
Hands-on experience with DBT (or similar transformation frameworks).
Hands-on experience with Python and orchestration frameworks (Airflow, Dagster, Prefect).
Familiarity with modern cloud data warehouses (Snowflake, BigQuery, Redshift, etc.).
Experience with BI tools (Metabase, Superset, Tableau, etc.).
Understanding of data quality, governance, and observability practices.