Principal Business Intelligence Engineer

Zillow Zillow · Consumer · United States · Remote

This role focuses on building and scaling the business intelligence and analytics engineering practice at Zillow. The Principal BI Engineer will design semantic layer architecture, ensure data consistency across BI, data science, and AI tools, and influence data infrastructure and tooling decisions. The role involves deep technical expertise, strategic vision, and cross-functional influence to support AI-powered analytics and business decision-making.

What you'd actually do

  1. Dive deep into Zillow's internal and third party data to model data that accurately reflect our customer journey and business processes.
  2. Design a reusable, modular semantic layer that makes metrics and dimensions consumable across BI tools, data science workflows, and AI systems, while promoting consistency across those surfaces.
  3. Lead cross-organizational data initiatives that align with company strategy and roadmap planning
  4. Drive alignment on metric definitions and data governance standards across business lines
  5. Influence build-versus-buy decisions for analytics tooling, semantic layer platforms, and data governance systems

Skills

Required

  • 8+ years of professional experience in analytics engineering, data engineering, visualization, or a related technical data role
  • Experience shipping customer facing, production grade reporting on time and accurately every day.
  • Expert-level SQL and data modeling skills with experience designing data architectures that span multiple business domains
  • Excellent communication and partner management skills, with a consistent ability to gain alignment and influence across product development, engineering, analytics, finance, sales and operations.
  • Deep experience with semantic layer design, metrics-as-code patterns, and data governance at organizational scale
  • Strong understanding of how AI systems, conversational analytics tools, and machine learning workflows consume structured data
  • Experience evaluating and adopting analytics engineering tooling at the organizational level (dbt, Databricks, Snowflake, or similar)

What the JD emphasized

  • shipping customer facing, production grade reporting on time and accurately every day
  • Expert-level SQL and data modeling skills
  • Deep experience with semantic layer design, metrics-as-code patterns, and data governance at organizational scale
  • Strong understanding of how AI systems, conversational analytics tools, and machine learning workflows consume structured data
  • Experience evaluating and adopting analytics engineering tooling at the organizational level