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About
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
Qualifications
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
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
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Languages
- English
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