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Staff Data Engineer

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EMP:Technology
London - Hybrid
Tiempo Completo
Remoto
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MoonPay MoonPay is for builders with something to prove

This isn't a "work on cool crypto stuff" company.

It's a high-standards, high-velocity, high-accountability company building the operating system for value movement.

If the internet moves information, we move value: crypto, stablecoins, tokenized assets, and whatever comes next.

Four offerings make that real: fund, tokenize, trade, and spend.

30M+ customers and 500+ ecosystem partners run on us.

Licensed in the U.

Regulated across the UK, EU, Canada, and Australia.

AI is the default operating mode here.

It's woven into every role, and we expect you to use it daily.

It handles the manual work so you can deliver on what actually matters.

You'll thrive here if outcomes excite you more than process, if impact motivates you more than titles, and if you want hard problems, real ownership, and teammates who love winning, building, and doing it together.

The bar is high.

The pace is real.

We're building for what's next, for humans and agents.

Recent recognition: Forbes' America's Best Startup Employers 2026.

2nd in Crypto Services on Fortune's inaugural Crypto 100, The Sunday Times Best Places to Work two years running.

Research has shown that women are less likely than men to apply for this role if they do not have experience in 100% of these areas.

Please know that this list is indicative, and that we would still love to hear from you even if you feel that you are only a 75% match.

Habilidades

can be learned, diversity cannot. ______________________________________________________________________________________________________ 1

About the Opportunity ✍️  This is a hands-on technical leadership role with the opportunity to shape the long-term direction of our data platform.

You will lead the design and evolution of the systems that power analytics, product insights, integrations, and machine learning across MoonPay.

Working across teams, you’ll solve complex challenges spanning architecture, reliability, scal.

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