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 P&G 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.

THE ROLE

We are looking for a Data & Analytics Engineer to provide hands-on analytics engineering expertise in designing, building, and migrating analytical processing pipelines and data models—including data marts, multi-dimensional models, and KPI implementations—from SAP BusinessObjects to Sigma.

The role focuses on delivering high usability, strong performance, and robust data governance within a modern Snowflake-based cloud data stack, enabling scalable self-service analytics for business users.

Responsibilities: 

• Design, build, and optimize high-performance Data Marts (Gold layer) within  Snowflake to deliver and support analytics-ready datasets 
• Develop and maintain analytics-ready data models using Airflow, Python, Snowflake, SQL, and dbt
• Develop and maintain Snowflake Semantic Views for self-service analytics in Sigma in collaboration with business stakeholders
• Partner with business stakeholders to define, redesign, and implement standardized KPIs
• Support the migration from SAP BusinessObjects to Sigma
• Ensure alignment with data governance, performance, security, and scalability standards
• Work closely with BI, data engineering, and business stakeholders to translate business requirements into robust analytical models
• Contribute to business user enablement through best practices, data structures, and documentation
• Support multiple project phases in parallel with a pragmatic, delivery-focused mindset

Requirements

Technical Skills

• 4+ years of hands-on experience as a Data Engineer and/or BI Engineer in modern cloud data environments
• Advanced SQL skills 
• Deep understanding of the Snowflake Cloud Data Platform
• Experience working with Airflow or similar orchestration tools
• Practical experience with dbt for data mart development and analytics modeling
• Solid understanding of data modeling concepts, including dimensional models and KPI frameworks

Business & Collaboration

• Proven experience working with cross-functional teams (BI, data engineering, and business stakeholders) to deliver analytics solutions end-to-end
• Ability to translate business requirements and KPIs into scalable data models and semantic layers
• Strong communication skills, enabling effective collaboration during requirements clarification, model design, and KPI validation
• Strong sense of ownership and a proactive approach to identifying and solving data quality, modeling, or performance issues
• Self-driven and proactive, with the ability to co-lead analytics and modeling topics together with internal BI teams
• English proficiency: Upper-Intermediate and above

Nice to have:

• Experience migrating from SAP BusinessObjects or similar legacy BI platforms
• Hands-on experience with modern BI tools

Benefits

Why people stay

First, the foundation:

• Remote flexibility: Work where and how you work best - we trust you to deliver
• Fair compensation: Competitive salary + benefits that matter (medical, learning)

Then, the growth:

• Ownership opportunities: See a problem worth solving? Own it. We back smart risks over bureaucratic safety
• AI enhancement: We leverage AI to make you faster and stronger - complementing your abilities, not replacing them
• Learning investment: English classes, professional development
• Career progression: Real paths up, not just sideways shuffling

Finally, the people:

• Reliable teammates: No radio silence, no "not my problem" attitudes
• Supportive culture: When you're stuck, people help. When things break, we fix them together
• Human connections: Regular meetups, tech talks, and actual relationships beyond work

Curious? We are too. Let's talk