Senior Data Analytics Engineer

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.

• 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.

Nice to Have

• Experience in a federated or data mesh environment.
• Familiarity with data catalog tools (DataHub, Collibra, Amundsen).
• Exposure to analytics in domains like marketing, CRM, or B2B reporting.

• Attractive compensation package consisting of base salary and the potential to earn a significant bonus for top performance
• Stock options
• Responsibility from day one and professional and personal growth
• Opportunity to have a real impact in a high-growth global category leader
• 40% discount on all Fever events and experiences
• Home office friendly
• Health insurance and other benefits such as Flexible remuneration with a 100% tax exemption through Cobee
• English Lessons
• Gympass Membership
• Possibility to receive in advance part of your salary by Payflow

Interview Process

The interview process will be conducted in Spanish; however, some interviews will require English.

• Talent Interview
• Technical Interview I
• Technical Interview II
• Manager Interview

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.