Analytics Engineer

Job Description

REQUIREMENTS

• Analytics Engineering fundamentals — you’re strong in dbt and SQL, especially dimensional modeling; you’ve shipped production-grade models other teams build dashboards on top of
• Comfortable pushing back — you know how to challenge a stakeholder request that would hurt data quality, without shutting down the relationship
• Built for scale, not just speed — you design models that hold up months later, and know when “good enough now” beats “perfect later”
• AI-native work style — you use AI tools beyond just chatting, to speed up modeling, documentation, or test generation
• Appetite for ownership — you’re ready to take projects end-to-end, and, if senior, to help raise the team’s standards too

RESPONSIBILITES

• Build data models Business Analytics teams trust — design and ship dbt models and tests that hold up under real, everyday use across Product, Growth, and Ops Finance
• Partner with Business Analysts, not just execute for them — understand what they actually need, and push back when a request would trade long-term reliability for a quick fix
• Reduce technical debt at scale — help migrate parts of the data stack to a more scalable setup, including our ongoing move to Omni
• Own your projects end-to-end — take work from discovery through delivery, and follow up on its real impact instead of just closing a ticket
• Scale your own workflow with AI — use AI tools to speed up documentation, testing, and modeling work, while keeping the judgment calls in your hands

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