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Head Of Data

Fundraise Up•United States•🌍 Remote
Full-time7-15
$224K - $245K
per year
👁️ 0 views•📝 0 applications•Posted 10/9/2026•Expires 12/8/2026
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Job Description

About Fundraise Up We're Fundraise Up , a global fundraising platform built to make donating to nonprofits fast, seamless, and accessible to all. Every month, our technology powers tens of millions of dollars in donations across the globe.

Many of the world's leading nonprofits trust our platform, including UNICEF, the Alzheimer's Association, and a wide range of global NGOs, and we hold a 4. 9/5 rating across top software review platforms. Our mission is to unlock the world's generosity potential by optimizing how people give.

About the Role

AI is only as good as the data underneath it. This role makes ours trustworthy. As our Head of Data, you'll build and guarantee the data foundation the whole company builds on: the pipelines, the models, the definitions, and the contracts that let people and AI agents trust what they're looking at.

You'll report to our CFO, which keeps you neutral to any single function and close to how the business actually runs and measures itself. This is a player-coach seat.

You'll write code and do the hardest technical work yourself, ship a major internal AI-powered initiative every quarter alongside our AI Transformation team, and grow this into a full function as it proves its value.

Key Responsibilities

Own the data infrastructure, hands-on. Design, build, and run the pipelines and ETL/ELT that feed our warehouse. Own freshness, reliability, and cost. Treat the infrastructure as never finished, and keep making measurable gains in coverage, latency, and reliability. Build the trusted data layer everyone relies on.

Own the data models, tests, validation, observability, and lineage that prove the data is accurate, plus the consistent metrics that give two teams the same answer to the same question. Make it self-serve and document it well enough that PMs, analysts, internal builders, and AI agents can answer their own questions.

Own the definitions library. Teams own their definitions; you give them a single standardized, versioned home. Se

Required Skills

data infrastructurepipelinesETLELTdata modelsdata validationdata observabilitydata lineagemetricsdefinitions libraryAIinternal AI-powered initiative

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