Staff Analytics Engineer
Preply - Barcelona, Catalunya, Spain
Posted Feb 2, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Staff Analytics Engineer Barcelona, Catalunya, Spain We power people's progress. At Preply, we're all about creating life-changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it's creating real impact. We've just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human-led, AI-enhanced learning. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries - and we're only getting started. As a category-defining company, we're shaping what the future of learning looks like at global scale. Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day. Meet the team! At Preply, data is foundational to how we build, experiment, and scale our product. We run hundreds of A/B tests at any given time , power a complex two-sided marketplace , and increasingly rely on data to enable AI-driven personalization and decision-making . Our analytics platform supports teams across Product, Growth, Finance, and Engineering/AI, and its quality directly impacts the speed and confidence of company-wide decisions. As a Staff Analytics Engineer , you will play a critical role in shaping the analytical foundations of Preply . You'll operate at a company-wide level, setting standards, designing scalable data models, and influencing how analytics engineering is practiced across teams.
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