Senior Analytics Engineer (Semantic Layer)
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Summary
Senior Analytics Engineer who designs and builds the semantic/metrics layer on top of the core data platform: creating reusable, tested semantic models, governing business metrics with stakeholders, and delivering dashboards and analytical products. Core stack is advanced SQL, dbt-style transformations, and modern cloud data platforms.
- 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