Principal BI Engineer

Prodege, LLC is a cutting-edge marketing and consumer insights platform that helps brands and agencies uncover business insights. The Principal BI Engineer is responsible for architecting and scaling the BI and analytics platform to improve performance and reliability while enabling self-serve analytics with strong governance.

Responsibilities:

• Architect and scale Prodege’s BI and analytics platform for long-term performance and reliability
• Design high-quality analytics data models that power consistent and trusted reporting
• Enable fast, self-serve analytics without compromising governance or data integrity
• Partner with Product, Data Science, and business teams to translate needs into durable solutions
• Raise the bar on analytics engineering standards, tooling, and best practices
• Leverage AI-based development and analytics tooling to accelerate delivery and quality
• Design, build, and maintain scalable BI and analytics architectures
• Develop and manage dbt models on Snowflake, ensuring performance, accuracy, and maintainability
• Write, optimize, and tune complex SQL queries for large-scale datasets
• Build and maintain dashboards, metrics, and semantic layers using Sigma
• Work closely with Product and Data Science to define metrics, KPIs, and reporting requirements
• Implement analytics engineering best practices (testing, version control, documentation, code reviews)
• Enable and support self-serve analytics while enforcing metric consistency and governance
• Leverage AI-powered tools to improve development velocity, validation, and documentation
• Mentor BI and analytics engineers and influence engineering standards across the organization

Requirements:

• Bachelor's degree in Computer Science, or related area of study
• Eight or more (8+) years of experience in BI, Analytics Engineering, or Data Engineering
• Strong hands-on expertise with Snowflake, dbt, Sigma (or comparable BI tools with semantic modeling experience), and Advanced SQL optimization
• Experience building production-grade analytics solutions, not just ad-hoc reports
• Strong understanding of analytics architecture, data modeling, and performance tuning
• Proven ability to collaborate with Product, Data Science, and business stakeholders
• Experience using AI-based tooling to enhance analytics or developer productivity
• Experience in ad tech, performance marketing, marketplaces, or consumer platforms
• Familiarity with streaming or near-real-time analytics architectures
• Experience enabling analytics governance and metric standardization at scale
• Mentorship or technical leadership experience
• Exposure to ML-driven analytics or experimentation platforms