Senior Analytics Engineer

🕒 August 4

🇺🇸 United States – Remote

💵 $151.7k - $242.3k / year

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 43%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Zillow

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2006

🏠 Real Estate

🛍️ eCommerce

👥 B2C

💰 $4.1M Post-IPO Equity on 2012-12

Real Estate • eCommerce • B2C

Zillow is a leading real estate and property rental marketplace that provides comprehensive information on homes, apartments, and properties for sale or rent. It offers users tools to search for properties, calculate mortgage rates, and connect with real estate agents. The platform also features innovative algorithms that provide Zestimates, which are estimated market values of homes. Zillow is a go-to resource for individuals looking to buy, sell, or rent properties, as well as for agents and brokers who want to reach a wider audience.

📋 Description

• Lead the design, development, and maintenance of trusted, scalable analytical data products • Build reusable data models, standardized metrics, and semantic layer components • Support business intelligence, self-service analytics, data science, and AI-powered interfaces • Translate complex business requirements into well-structured data models and precise metric definitions • Implement business logic consistently across teams and analytical surfaces • Partner with Data Engineering, Data Science, Business Intelligence, Product Management, and business stakeholders • Prioritize analytics engineering initiatives and define technical requirements and data contracts • Manage cross-team dependencies • Improve data quality, governance, discoverability, and documentation • Build, optimize, and operate last-mile data transformation pipelines • Use version control, code review, CI/CD, automated testing, monitoring, and alerting • Mentor and coach teammates on data modeling and engineering best practices • Contribute to analytics engineering standards and roadmap decisions • Enable stakeholders to confidently use governed 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 • Experience owning analytical data products across multiple data domains end-to-end • Ability to solve complex data modeling and metric definition challenges independently • Ability to lead cross-functional workstreams and translate business needs into technical specifications • Ability to prioritize competing requests and manage multiple projects and upstream dependencies • Deep proficiency in SQL • Experience with dbt or equivalent data transformation frameworks • Knowledge of dimensional, denormalized, and entity-relationship modeling • Experience with Databricks or Snowflake • Proficiency in Git • Experience with version control, CI/CD, code review, automated testing, data quality checks, monitoring, and root-cause analysis • Experience designing and maintaining semantic layer components, metrics-as-code, and metadata • 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 and align stakeholders on shared metric definitions • Ability to write concise self-service documentation and mentor teammates • Experience using AI-assisted coding tools and validating generated SQL, transformation logic, and documentation

🏖️ Benefits

• Equity awards based on factors such as experience, performance and location • Remote work from a physical location of the employee’s choice • Flexible work from wherever employees are most productive • Equal employment opportunity and disability accommodations