Data Engineer

Want to help us help others? We’re hiring! 

GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.

Join us! The GoFundMe team is searching for our next Staff Data Engineer to join our Analytics Engineering squad within the Data team. In this role, you’ll help make our data reliable, high-performing, and easy to use for analysts, scientists, engineers and business teams. You’ll also explore using AI to assist our team in building and maintaining data models, ensuring we move fast without sacrificing quality. You’ll have a unique chance to own the normalized layer, improve how we monitor and test our models, and shape the way our analytics work at the company.

This is a hybrid position. Candidates considered for this role will be located in Buenos Aires, Argentina.

The Job

• Own and improve our normalized data layer, ensuring consistency, scalability, and high performance.
• Build automated tests and monitoring to catch issues before they reach production.
• Work closely with engineers, analysts and scientists to ensure data pipelines and models produce accurate, consistent, and well-structured data, coordinating on model design, testing, and quality checks to support reliable reporting and analytics.
• Contribute to warehouse performance and cost optimization, helping ensure queries are fast, reliable and efficient.
• Explore ways to use AI to help the team design models, generate code suggestions, review changes, and detect anomalies.
• Maintain clear documentation and standards so everyone on the team can move fast with confidence.

You

• 8+ years as a data engineer crafting, developing and maintaining business data warehouse alternatives consisting of structured and unstructured data.
• Proficiency with building and orchestrating data pipelines using ETL/data preparation tools.
• Strong SQL and python skills.
• Experience with data observability, automated testing, and monitoring frameworks.
• Comfortable with Snowflake performance tuning and managing large datasets.
• Collaborative and proactive — you like helping teams move faster and more reliably.
• Fluent in English (written and spoken).
• Familiarity with BI tools (Looker, Hex, Mode, Tableau) and semantic layers.
• DBT experience.