SS
Sigma Software
Analytics Engineer

Senior Analytics Engineer (Semantic Layer)

HybridSeniorAnalytics Engineerposted 1w ago
Role summaryAI-generated

This role focuses on architecting scalable semantic layers that bridge business requirements with technical implementations, ensuring metrics are accurate, reusable, and optimized for cross-functional analytics teams. The engineer will drive data standardization while collaborating closely with stakeholders to translate complex business definitions into maintainable, testable, and high-performance analytical assets.

Skills required

About this role

  • 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

Qualifications

  • 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

Additional Information

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

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