Staff Analytics 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 Analytics Engineer to join our Data Platform team! In this position, you will help define and scale our modern analytics layer—bridging raw data and business insights through trusted, well-modeled, and accessible datasets. This role sits at the intersection of data engineering, analytics, and product, and is critical to enabling high-quality decision-making across the organization. You’ll partner closely with stakeholders to define metrics, model data, and build scalable, self-serve analytics foundations. This, in turn, drives business growth, fostering a worldwide environment of peer-to-peer generosity. This is a hybrid position. Candidates considered for this role will be located in Buenos Aires, Argentina. The Job Design, build, and maintain scalable data models that power analytics, reporting, and experimentation Develop and manage transformation workflows using DBT (or similar tools) following modern ELT practices Define and maintain a metrics layer / semantic layer to ensure consistent, trusted business definitions Build curated, analytics-ready datasets from multiple sources (event data, transactional systems, third-party APIs) Partner with stakeholders to translate business questions into well-defined metrics and data models Ensure data quality through testing, validation, and monitoring frameworks Optimize query performance and cost efficiency within Snowflake (or similar warehouse) Enable self-service analytics by designing intuitive, well-documented data models Support and scale experimentation frameworks, including A/B testing and metric standardization Leverage AI tools such as Claude and agentic workflows to accelerate data modeling, metric documentation, and semantic layer development Help shape how the team uses AI-assisted analytics — enabling data scientists and business users to query trusted datasets through governed AI interfaces Collaborate with data engineers to define upstream data contracts and improve data reliability Document data models, metrics, and lineage to improve discoverability and trust Contribute to governance practices including naming conventions, versioning, and access controls Drive adoption of best practices in analytics engineering across the organization You 5+ years of experience in analytics engineering, data engineering, or advanced analytics roles Strong expertise in SQL (advanced querying, optimization, window functions, etc.) Hands-on experience with DBT or similar transformation frameworks Experience working with modern data warehouses such as Snowflake, BigQuery, or Redshift Strong understanding of data modeling best practices (star schema, dimensional modeling, etc.) Hands-on experience with AI-assisted development tools such as Claude or GitHub Copilot to accelerate modeling, documentation, and code review Strong understanding of how LLMs and agentic workflows interact with semantic layers and what that means for how analytics data is structured and governed Experience defining and managing business metrics and semantic layers Familiarity with event-based data models and user behavior tracking Experience working with analytics tools such as Looker, Tableau, Sigma, or similar Preferred Experience with experimentation platforms and A/B testing frameworks Familiarity with metrics layer tools (e.g., LookML, MetricFlow, Cube, Transform) Experience with event tracking tools (GA, Heap, Segment, CDPs) Experience with Python for data transformation or analysis Knowledge of data orchestration tools (Airflow, Prefect) ... (truncated, view full listing at source)