Analytics Engineer

🔥 10 hours ago

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51 - 200 employees

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📋 Description

• Design and maintain scalable star schemas within our SQL Server data warehouse, ensuring clarity and long-term maintainability • Define and rigorously enforce grain discipline across all fact tables • Architect and optimize Power BI semantic (Tabular) models for cross-company usage • Define, formalize, and document core business KPIs across Revenue, Conversion, Retention, Payments, and Finance • Establish and fully own a governed metric layer managed by BI • Create and maintain a structured KPI registry with approved measures, dimensions, and filters • Design the semantic layer to enable controlled AI access to metrics—without exposing raw tables or ambiguous logic • Ensure AI tools can safely and consistently answer analytical questions using governed definitions • Improve dataset performance through aggregations, partitioning, and incremental refresh strategies • Eliminate metric duplication and resolve conflicting definitions across reports • Provide architectural guidance to analysts building on top of the semantic layer • Contribute to long-term BI platform and analytics architecture decisions

🎯 Requirements

• 7+ years of experience in Analytics Engineering, BI Architecture, or advanced BI development • Deep expertise in dimensional modeling (Kimball methodology, star schemas, fact/dimension design, grain definition) • Strong hands-on experience with Power BI semantic models (Tabular, measures, relationships, perspectives) • Advanced SQL skills with strong performance awareness • Proven experience deg and governing metric layers in production environments • A systems-thinking mindset with structured, architectural discipline • Experience building analytics foundations that scale across multiple departments • Clear communication skills and the ability to document complex logic with precision

🏖️ Benefits

• Remote-first collaboration aligned with EU time zones • Direct impact on company-wide decision-making systems • The opportunity to define how AI interacts with business data • A culture that values structure, clarity, and long-term thinking over quick fixes • Close partnership with leadership and cross-functional teams • The chance to build something foundational, not incremental • Annual company sailing week in the Mediterranean + team meetups across the EU