Analytics Engineer (dbt/Snowflake) (f/m/d)

Analytics Engineer (dbt/Snowflake) (f/m/d)

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

Requirements:
• 3+ years of hands-on experience in analytics engineering, data engineering, or highly technical analytics roles
• Strong SQL proficiency, including advanced CTEs, window functions, complex joins, and query optimization
• Proven production experience with dbt, including Jinja, macros, and incremental models
• Hands-on experience with Snowflake
• Experience designing layered data models (staging, intermediate, marts)
• Strong understanding of data modeling principles and reusable analytical architecture
• Experience with version control using Git, including branching, pull requests, and rebasing
• Ability to translate business questions into technical data requirements
• Strong attention to documentation and data quality practices
• Experience working with modern ELT pipelines and analytical workflows

Nice to have

• Experience with Fivetran
• Experience with BI tools such as ThoughtSpot, Tableau, or Power BI
• Familiarity with semantic layer design and governed metrics
• Experience working with enterprise reporting layers
• Exposure to root cause analysis of data issues in production environments
• Experience supporting business stakeholders directly in analytical projects

Benefits:
What We Offer

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, well-being support
• Career progression: Real paths up, not just sideways shuffling

Finally, the people:

• Responsive teammates: No ignored Slacks, 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