Principal Business Intelligence Engineer

About the role

At Zillow Group, we are constantly innovating ways to operate, monetize, and improve our nationwide real estate marketplace. The Data Science, Analytics and Engineering team supports several lines of business across the company by partnering closely with business leaders and engineering to model, analyze, and visualize business relevant metrics that inform both short- and long-term decision-making. Our structure is very flat and you will soon find yourself interacting directly across a wide variety of roles. As a Principal Business Intelligence Engineer, you will shape the practice itself, defining how BI and analytics engineering scales across the company and how our data infrastructure evolves to meet the demands of AI-powered analytics. You will build a deep understanding of our mission, business model, and customers to identify opportunities to simplify processes, improve alignment, and strengthen our metrics platform. You will design semantic layer architecture that enables consistent, trusted data across BI, data science, and AI tools, while leading cross-organizational initiatives and influencing tooling and infrastructure decisions. This role requires deep technical expertise, strategic vision, and strong influence across teams. You Will Get To Dive deep into Zillow's internal and third party data to model data that accurately reflect our customer journey and business processes. 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. Lead cross-organizational data initiatives that align with company strategy and roadmap planning Drive alignment on metric definitions and data governance standards across business lines Influence build-versus-buy decisions for analytics tooling, semantic layer platforms, and data governance systems Mentor senior analytics engineers as well as shape strategic direction and technical standards for analytics engineering across the organization Partner with executive stakeholders to influence how the data infrastructure must evolve to support company objectives Operate high availability data and reporting within SLA through quality alerting, detecting issues before customers and resolving with a sense of urgency. This role has been categorized as a Remote position. "Remote" employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions. In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $168,600.00 - $269,400.00 annually. This base pay range is specific to these locations and may not be applicable to other locations. In Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont the standard base pay range for this role is $160,200.00 - $256,000.00 annually. The base pay range is specific to these locations and may not be applicable to other locations. In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.

Requirements

• 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)
• Here at Zillow - we value the experience and perspective of candidates with non-traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences.
• Get to know us
• At Zillow, we're reimagining how people move-through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech

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