Senior Analytics Engineer

Role Overview

The Data team at Zillow turns complex data into insights, models, and data products that help power smarter decisions across the business. As part of our broader Data Analytics and Insights organization, this team partners closely with product, engineering, and business leaders to solve meaningful problems, improve the quality and usability of our data, and build scalable solutions that create impact for customers and employees alike.

What You Will Do

Lead the design, development, and maintenance of trusted, scalable analytical data products, including reusable data models, standardized metrics, and semantic layer components that support business intelligence, self-service analytics, data science, and AI-powered interfaces.

Why It Might Be a Fit

The ideal candidate will have 5+ years of experience in analytics engineering, data engineering, business intelligence, or a closely related field, working with large datasets to develop reliable analytical data models and data products.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Information Systems, Statistics, Business, or a related field.
• 5+ years of experience in analytics engineering, data engineering, business intelligence, or a closely related field, working with large datasets to develop reliable analytical data models and data products.
• Demonstrated experience owning analytical data products across multiple data domains end-to-end and independently solving complex data modeling and metric definition challenges.
• Proven ability to lead cross-functional workstreams, translate business needs into technical specifications, prioritize competing requests, and manage multiple projects and upstream dependencies in alignment with team and business goals.
• Deep proficiency in SQL, data transformation frameworks such as dbt or equivalent, and analytical modeling approaches, including dimensional, denormalized, and entity-relationship models, with sound judgment about granularity, aggregation, reuse, and business logic placement.
• Experience working in online data lakehouses like Databricks or Snowflake and proficiency in Git
• Strong experience applying software engineering and operational practices to analytics workflows, including version control, CI/CD, code review, automated testing, data quality checks, monitoring, and root-cause analysis, with the ability to improve team standards and reliability.
• Experience designing and maintaining semantic layer components, metrics-as-code, and metadata for multiple consumers, with an understanding of data governance and how BI tools, data science workflows, and AI-powered interfaces interpret metric definitions.
• Ability to communicate technical trade-offs clearly, align stakeholders on shared metric definitions, write concise self-service documentation, and mentor teammates on modeling and engineering best practices.
• Experience using AI-assisted coding tools with the judgment to validate generated SQL, transformation logic, and documentation, prevent duplicated or inconsistent business logic, and independently explain and defend your design decisions.

Benefits

• Competitive base salary
• Equity awards based on factors such as experience, performance, and location
• Health insurance
• Vision insurance
• Dental insurance
• 401(k) or other retirement plan
• Paid time off
• Paid holidays
• Flexible work arrangements
• Professional development opportunities

Tagged as: Data Analysis, Snowflake, SQL