Principal Analytics Engineer

As a Principal Analytics 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.

Responsibilities

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.

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)

Nice to have

Non-traditional backgrounds; transferable skills or related experiences

Benefits

Equity awards