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Fever is the world's leading tech platform for culture and live entertainment, operating in 55+ countries with 300+ million monthly users. The company partners with major brands like Netflix, F.C. Barcelona, and Primavera Sound, and is backed by leading global investors.
As an Analytics Engineer, you will serve as the bridge between data engineering and business analytics, ensuring stakeholders can make decisions based on reliable, well-modeled, and discoverable datasets. You'll work within a federated data organization that balances centralization with autonomy across modern data platforms including Snowflake, DBT, Airflow, DataHub, and Metabase.
Key responsibilities include:
- Design, build, and maintain data models using DBT and SQL to 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)
- Partner with business squads (B2B, Marketing, CRM, Product) to understand needs and create reusable data assets
- Ensure data quality and consistency through testing frameworks, observability, and governance practices
- Enable self-service analytics by supporting stakeholders in exploring data through existing BI tools or driving custom developments
- Contribute to Airflow pipelines in Python for automation and orchestration
- Help shape the company's data mesh vision by creating domain-owned datasets while following platform guidelines
The role is based in Argentina with home office flexibility anywhere in the country. You'll work in a young, international team in a fast-paced, high-growth environment.
REQUIREMENTS:
- Fluent in Spanish and English (required for communication with local and global teams)
- Bachelor's, Master's, or PhD in Computer Engineering, Data Engineering, Data Science, or related field
- Strong SQL skills and data modeling experience (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)
- Experience with BI tools (Metabase, Superset, Tableau)
- Understanding of data quality, governance, and observability practices
- Collaborative mindset comfortable working with engineers and business stakeholders
- Strong communication skills adaptable to multidisciplinary, international, fast-paced environment
- Keen interest in understanding complex business landscapes and driving company forward through data
NICE TO HAVE:
- Experience in federated or data mesh environments
- Familiarity with data catalog tools (DataHub, Collibra, Amundsen)
- Exposure to analytics in marketing, CRM, or B2B reporting domains
