About ITRex

THE PLACE

ITRex - AI pioneers who build systems that actually work in the real world, not just in demos. We're 250+ people spread across the US and Europe, creating solutions for companies like Procter & Gamble and Shutterstock. We keep it simple, build it right, and focus on what works.

THE PEOPLE

We're the kind of people who don't ignore messages in Slack, who jump in to help when you're stuck on a problem, and who offer solutions instead of blame when things go sideways. We believe in openness, accountability, and having each other's backs. No office politics, no hidden agendas - just people who care about doing good work together and supporting each other to get there.

About The Job

We are looking for a skilled Analytics Engineer to help build scalable, trusted, and business-ready data foundations for one of our long-term international clients.

In this role, you will work at the intersection of data engineering and business analytics, transforming raw data into well-structured analytical models that support reporting, self-service analytics, and enterprise decision-making.

The ideal candidate combines strong SQL depth with hands-on experience in modern data stack tools, especially dbt, and knows how to design reusable data models that balance technical quality with business usability. This role requires strong ownership, attention to data quality, and the ability to collaborate directly with stakeholders to translate business requirements into reliable analytical solutions.

Your Responsibilities

• Design and maintain modular data models using dbt across staging, intermediate, and marts layers
• Develop performant SQL transformations that support scalable analytical workflows
• Build reusable and well-documented data assets for business consumption
• Implement data quality checks and custom tests to improve trust in analytical outputs
• Collaborate with stakeholders to define technical requirements from business needs
• Maintain clear documentation for analytical models and business logic
• Participate in peer reviews and maintain clean version control practices
• Support metric consistency and standardization across reporting environments
• Investigate data anomalies and trace issues to root causes across upstream systems
• Deliver analytical assets that serve as a trusted foundation for reporting and decision-making