Senior Staff Data Platform Architect

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 Senior Staff Data Platform Architect to help design and evolve the modern data platform that powers analytics, product decision-making, experimentation, and AI/ML across GoFundMe.

This is a highly impactful role focused on modernizing our existing data ecosystem into a scalable, cloud-native foundation for real-time insights, experimentation, trust and safety, and AI-driven experiences. You’ll partner closely with engineering, product, analytics, and data science to build systems that are reliable, efficient, and built for long-term growth.

AI is increasingly embedded in how we build, prioritize, and ship across Product and Technology, and this role will help create the data foundation that enables those capabilities to scale responsibly, reliably, and effectively.

Candidates considered for this role will be located in the San Francisco, Bay Area. There will be an in-office requirement of 3x a week.

The Job

• Modernize and evolve our existing data ecosystem into a scalable, secure, and high-performing cloud-native platform.
• Own end-to-end data platform architecture across ingestion, transformation, modeling, storage, and consumption.
• Design systems that support analytics, real-time reporting, experimentation, trust and safety, and AI/ML use cases.
• Define enterprise-wide standards for data modeling, semantic layers, and trusted datasets used across the business.
• Build practical frameworks for data lineage, quality, privacy, and security, including support for GDPR, CCPA, and other compliance needs.
• Drive reliability, observability, and cost efficiency across the platform to support growth at scale.
• Guide technology decisions across data engineering, analytics, and AI use cases, including evaluation of modern tools and architectural patterns.
• Partner cross-functionally with engineering, product, analytics, and data science teams to translate business needs into scalable technical solutions.
• Stay hands-on in architecture and design decisions, helping solve complex platform problems when needed.
• Mentor engineers and raise the technical bar across the data organization by coaching on best practices and influencing strategic platform decisions.

You

• 10+ years of experience in data architecture, platform engineering, or data engineering, with at least 3+ years in a senior, staff, or architect-level role.
• Proven experience building and evolving data platforms end-to-end, including architecture, data models, and platform standards — not just individual pipelines.
• Hands-on experience with modern cloud-native data platforms such as Snowflake, Databricks, or similar technologies.
• Strong understanding of data modeling, semantic layers, and building trusted datasets for analytics and product use cases.
• Experience designing both batch and real-time data systems, including streaming or event-driven architectures.
• Leverage AI tools such as Claude and agentic workflows to accelerate architectural design, technical documentation, and platform delivery.
• Experience implementing data governance in practice, including lineage, data quality, access controls, and privacy/compliance frameworks.
• Strong communicator who can explain architecture decisions clearly to engineers, product managers, and leadership.
• Demonstrated ability to communicate complex technical concepts clearly and drive alignment across diverse stakeholders.
• Experience influencing technical direction across teams and aligning stakeholders such as AI Platform and other engineers around shared platform decisions.
• Comfort operating in a hands-on technical leadership role, balancing strategy with execution.
• Familiarity with AI-assisted development practices, using tools like Cla