Senior Analytics Engineer

Senior Analytics Engineer

Required skills

• SQL expert

• dbt strong

• Semantic Modeling expert

• Business Intelligence strong

• Analytics Engineering expert

• 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.

Requirements

• 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

Responsibilities

• 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