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Argentina
Live, first seen by us 18 days agoAt Fever, we are building a federated data organization that combines centralization where it’s essential and autonomy where it creates value.
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.
Design, build and maintain DBT/SQL data models for clean, trusted datasets
Define and certify business-critical metrics with the data engineering team
Turn business squads' needs into reusable data assets
Enable self-service analytics through existing BI tools or custom builds
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.
Design, build, and maintain data models (DBT, SQL) that transform raw data into clean, trusted datasets
Collaborate with the data engineering team to define and certify business-critical metrics
Work with business squads (B2B, Marketing, CRM, Product) to understand their needs and turn them into reusable data assets.
Support self-service analytics by enabling stakeholders to explore data confidently
Strong communication skills, adaptable to a multidisciplinary, international, and fast-paced environment.
Experience in a federated or data mesh environment.
Strong experience with SQL and data modeling (star/snowflake schemas, data vault, or similar).
Familiarity with data catalog tools (DataHub, Collibra, Amundsen).
Hands-on experience with DBT (or similar transformation frameworks).
Hands-on experience with Python and orchestration frameworks (Airflow, Dagster, Prefect).
- 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.
From the employer’s posting.
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Day 18
Similar jobs usually come down between day 6 and day 47.
From 1,409 similar postings that came down. Coming down is not always a hire.
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- 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.
- 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.).
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.).
- A deep understanding of data modeling and how complex backend systems generate and expose data across products and domains. - 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.).
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.
- 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.
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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 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.
This is a unique opportunity to join Fever’s Data team at a key moment of growth. You’ll help shape how data is modeled, governed, and consumed across multiple business domains — enabling thousands of decisions every day. You’ll work with a modern stack, learn from an experienced team, and have real impact on how we scale data across the company.
The interview process will be conducted in Spanish; however, some interviews will require English.
Thank you for considering joining Fever. We cannot wait to learn more about you!
If you want to learn more about us: Fever's Blog | Tech.Eu |TechCrunch
Fever is committed to creating an inclusive and diverse workspace where everyone's background and ideas count. Our main goal is to find the best possible talent regardless of place of birth, racial or ethnic origin, gender, gender identity, religion, opinion, sexual orientation, disability, pregnancy, marital status, age or caring responsibilities. We encourage everyone to apply!
If you require any kind of accommodation during the selection process please contact our Talent team so we can help you by providing a welcoming and seamless journey.
If you want to know more about how Fever processes your personal data, click here Fever - Candidate Privacy Notice
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Argentina
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