Senior Analytics Engineer (Semantic Layer)

Design and implement scalable semantic modeling approaches for enterprise analytics Build canonical analytical models on top of the core data platform Define and govern business metrics together with Finance, Product, Ad Operations, Sales, and other stakeholders Translate business definitions into robust and tested technical implementations Develop reusable semantic models consumable by BI tools, analytical products, and AI agents Create and maintain dashboards and analytical solutions for internal stakeholders Reconcile critical metrics across operational systems, reporting platforms, and financial data Implement automated testing for metrics, transformations, and business rules Maintain documentation, metadata, and lineage for business definitions and analytical assets Contribute to establishing company-wide data standardization processes Design intuitive datasets optimized for analyst workflows and machine consumption Support the evolution of self-service analytics capabilities Ensure governed metric definitions are consistently used across internal and customer-facing reporting systems At least 5 years of experience in Analytics Engineering or Data Engineering Strong background in analytics engineering, data modeling, or business intelligence engineering Advanced SQL skills Commercial experience with dbt or similar modern data transformation frameworks Strong understanding of dimensional, canonical, and semantic modeling concepts Experience building production-grade BI solutions and analytical products Experience collaborating with non-technical stakeholders to define business metrics and KPIs Strong understanding of data quality validation, testing, and reconciliation processes Ability to transform ambiguous business concepts into clear technical definitions Hands-on experience implementing semantic or metrics layers Experience in SaaS or AdTech domains Experience working with modern cloud-based data platforms and scalable analytics architectures At least an Upper-Intermediate level of English WILL BE A PLUS Finance and revenue reconciliation experience Experience with multi-tenant analytics environments Hands-on experience preparing structured data and metadata for AI/LLM consumption Experience building customer-facing analytics and reporting solutions PERSONAL PROFILE Strong analytical and problem-solving mindset Ability to work independently in a fast-paced environment Detail-oriented approach to data quality and business consistency Proactive communication and collaboration skills Ownership mindset and focus on long-term scalability