Senior Analytics Engineer

Overview

As a Senior Analytics Engineer, you'll build and own data models and metric definitions that support consumer analytics across marketing, lead generation, and site traffic. You'll establish trusted data products and semantic definitions for stakeholders, BI tools, data scientists, and AI systems.

What you'll do

• Build and maintain dimensional data models and metric definitions using SQL and dbt or an equivalent transformation framework.
• Establish metrics-as-code as an enterprise asset.
• Design data-quality tests, monitoring, and alerting so data products are trusted by default.
• Partner with data engineering to define upstream requirements and fix data-quality issues at the source.
• Work directly with US-based BI analysts, data scientists, and stakeholders to understand their actual needs.
• Define and evangelize semantic layer definitions for BI tools, data scientists, and AI systems.
• Own multiple data domains end to end.
• Mentor other engineers.
• Resolve metric governance across teams.
• Document transformation code, data products, and the foundation that people and AI systems build on.

What you'll need

• 5+ years of professional data experience, with deep semantic modeling or metric ownership.
• Expert SQL, with thought leadership about how grain, joins, and schema evolution affect relational modeling and metric implementation.
• Experience with dbt or an equivalent transformation framework.
• Experience with Git and CI/CD best practices.
• Comfort operating across a large time-zone gap, with proactive asynchronous communication and independent technical judgment.
• A track record of evolving how AI systems, conversational analytics tools, and machine learning workflows consume structured data.
• In-depth experience with cloud data platforms such as Databricks, Snowflake, or similar.
• In-depth experience with BI tools such as Tableau, Looker, or similar.

Details

• Office position in Bengaluru.
• Office employees regularly work at the Zillow India office for approximately 80 to 100 percent of their time each month.
• Employees must live within a reasonable commuting distance of the office.
• The role involves working with US-based colleagues across a large time-zone gap.