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

ITRex is an AI-focused company with over 250 employees across the US and Europe, delivering practical AI systems for clients such as Procter & Gamble and Shutterstock.

• 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

• 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