Senior Analytics Engineer (Semantic Layer)

Join a project where data consistency, analytics scalability, and AI readiness are treated as core business priorities. We are looking for a Senior Analytics Engineer to help build an AI-first semantic layer that standardizes business metrics across dashboards, reporting systems, analytical products, and AI-driven applications.

You will work closely with cross-functional stakeholders and engineering teams to transform raw data into governed business meaning that can be trusted across the organization.

We at Sigma Software offer the opportunity to contribute to large-scale AdTech and analytics initiatives, work with modern data platforms, and influence the future of self-service analytics and AI-powered reporting solutions.

CUSTOMER

Our Customer is a leading technology company operating in the AdTech and digital monetization domain. The company develops scalable self-service advertising and analytics solutions used by enterprise clients worldwide to manage campaigns, reporting, and monetization workflows. The environment combines large-scale data processing, analytics engineering, and AI-driven innovation, with a strong focus on trusted metrics, reporting consistency, and data governance.

PROJECT

The project focuses on building an AI-first semantic layer that standardizes and governs business metrics across analytics platforms, dashboards, reporting systems, and AI-powered applications. The team is developing canonical analytical models to ensure that concepts such as revenue, impressions, campaigns, and advertiser activity are consistently defined and reusable across the organization.

The initiative combines semantic modeling, modern data transformation practices, BI enablement, and AI/LLM-oriented data preparation. The goal is to establish a scalable analytics foundation that supports self-service analytics, trusted reporting, and future customer-facing analytical products.

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