Senior Analytics Engineer (Semantic… at Sigma Software · Bucharest

companyDescription
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.
jobDescription
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
additionalInformation
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