Principal BI Engineer

Prodege, LLC is a cutting-edge marketing and consumer insights platform that aids leading brands in uncovering business insights. The Principal BI Engineer role is essential for architecting and scaling Prodege’s BI and analytics platform, ensuring reliable reporting and self-serve analytics while maintaining governance and data integrity.

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 that support both standardized reporting and self-service analytics
• Define and guide the semantic / metrics layer strategy, including reusable metrics, governed KPI definitions, and trusted reporting foundations
• Architect BI capabilities that support executive / board reporting, experimentation, Product analytics, Growth, Yield, and business operations
• Guide teams on the right BI tools, semantic layer patterns, reporting structures, and data access models
• Continuously improve the performance, scalability, reliability, and cost efficiency of the BI environment
• Develop and manage dbt models on Snowflake, ensuring performance, accuracy, maintainability, and business usability
• Write, optimize, and tune complex SQL queries for large-scale datasets
• Design scalable analytics data models that support product, commercial, experimentation, and executive reporting use cases
• Ensure standardized business logic and durable data modeling patterns across reporting domains
• Build and maintain dashboards, semantic layers, and reporting assets using Sigma (or similar BI tools)
• Enable and support self-serve analytics while enforcing metric consistency, report usability, and governance
• Reduce dependency on engineering for routine reporting by creating reusable, well-governed data and metrics foundations
• Improve how the organization accesses, interprets, and uses data for decision-making
• Work closely with Product, Data Engineering, Data Science, Finance, Analytics, and business teams to define metrics, KPIs, reporting requirements, and semantic structures
• Translate business questions into scalable BI and analytics designs
• Support experimentation, product analytics, Growth, Yield, and executive decision-making through strong reporting foundations
• Implement analytics engineering best practices including testing, version control, documentation, code reviews, and semantic model governance
• Establish high standards for metric trust, report quality, maintainability, and consistency
• Mentor BI / analytics engineers and influence engineering standards across the organization
• Drive clarity and governance around KPI ownership and business logic changes
• Use AI-powered tools to improve development velocity, validation, query generation, documentation, insight summarization, and metric discovery
• Drive an AI-first mindset within BI by identifying where AI can meaningfully improve analytics workflows while maintaining strong human validation and business judgment
• Help teams use AI effectively to solve complex reporting, semantic modeling, and analytics problems

Requirements:

• Bachelor's degree in Computer Science, Engineering, Analytics, a quantitative discipline, or equivalent practical experience
• Eight or more (8+) years of experience in BI, Analytics Engineering, Data Modeling, or Data Engineering
• Strong hands-on expertise with Snowflake, dbt, Sigma (or comparable BI tools with strong semantic / metrics modeling experience), and advanced SQL optimization
• Proven experience designing and scaling modern BI platforms and reporting ecosystems, not just ad hoc dashboards or isolated reporting solutions
• Strong understanding of: Semantic / metrics layers, KPI standardization and governance, Analytics architecture and data modeling, Performance tuning and cost considerations in BI environments, Self-service BI design and trusted reporting foundations
• Experience building production-grade analytics solutions that support business-critical decision-making
• Proven ability to collaborate effectively with Product, Data Science, Data Engineering, Finance, Analytics, and business stakeholders
• Experience setting standards for reporting consistency, data quality, and semantic governance
• Strong mentoring and technical leadership experience with ability to influence architecture and BI practices across teams
• Experience using AI-based tooling to enhance analytics engineering, reporting workflows, developer productivity, or documentation quality
• Comfort working through ambiguity and helping define BI strategy in a greenfield or evolving environment
• Experience in AdTech, Performance Marketing, MarTech, marketplaces, or consumer internet platforms
• Familiarity with streaming or near-real-time analytics architectures
• Experience enabling analytics governance and metric standardization at scale
• Experience supporting experimentation platforms, product analytics, or Growth / Yield use cases
• Experience automating executive / board reporting
• Familiarity with AI-first / AI-assisted analytics and reporting workflows across BI teams