About the role

In this role, you will help shape the data layer behind Voyager, Zillow AI mode, by building high-scale data products that make trace and event data usable for analytics, evaluation, observability, and future learning systems. This role is a strong fit for an engineer who wants to improve AI quality, solve complex data platform challenges, and help define how AI system data is managed and used across Zillow.

You Will Get To

• Build and operate scalable data platforms and shared data products that power Zillow's next generation of AI experiences, especially Voyager / Zillow AI mode.
• Own and evolve trace and event data foundations that support analytics, online and offline evaluation, observability, governance, and future learning workflows.
• Design and operate production-grade batch, streaming, and near-real-time data pipelines using Databricks, Spark, Python, SQL, and modern lakehouse patterns.
• Improve platform reliability through schema management, data quality validation, alerting, anomaly detection, and production support for business-critical AI data products.
• Partner with engineering, analytics, and science teams to turn evolving AI data needs into reusable infrastructure and governed data products.
• Help define the long-term architecture for AI data systems, including data contracts, eventing patterns, retention approaches, and cleaner downstream interfaces.

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 $160,900.00 - $257,100.00 annually. This base pay range is specific to these locations and may not be applicable to other locations.In Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia the standard base pay range for this role is $152,900.00 - $244,300.00 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.

Who you are

• You have 5+ years of experience in big data engineering, data platform engineering, machine learning engineering, or a closely related field.
• You bring strong proficiency in Python and SQL and have experience building production-grade data systems on distributed platforms such as Databricks and Spark.
• You have designed and operated scalable batch, streaming, or near-real-time pipelines and datasets for analytics, observability, and AI or ML use cases.
• You have experience supporting ML, LLM, or agentic AI systems in production through high-quality data products, governance, and operational rigor.
• You are comfortable working with complex, high-volume event, telemetry, trace, or log-style datasets and with modern architecture patterns such as streaming, incremental processing, data contracts, or lakehouse design.
• You have improved production reliability through schema evolution, ingestion safeguards, monitoring, alerting, root-cause analysis, and operational ownership.
• You communicate clearly and collaborate effectively across engineering, analytics, science, evaluation, and platform teams in fast-moving environments.
• Experience with technologies and practices such as Kafka, Spark Structured Streaming, MLflow, OpenTelemetry, CI/CD, and Git-based workflows is a plus.
• 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.