Data Engineer

The Difference You Will Make

We are looking for Data Engineers who are passionate about making a difference through their work.

You will collaborate in a global, cross-functional environment and lead through influence and partnership to turn ideas into production-ready systems.

In this role, you will help develop and evolve search and experimentation platforms, prototype solutions, and adopt advanced data technologies.

Required Experience

• 3 5 years of hands-on experience in a software engineering role, shipping high-quality code to production
• Experience building or supporting high-scale, distributed systems, data pipelines, and/or analytical libraries

Technical Expertise: Programming & Data Engineering

Technical Expertise

• Proficiency in Java, Scala, and Python (at least one required; others preferred)
• Strong SQL expertise, with the ability to go deep when debugging or optimizing queries
• Proficiency with SQL-based analytics and big data technologies, including:
• Hive
• Presto/Trino
• Spark
• Deep, hands-on experience with at least one modern big data processing framework (e.g., Spark, Dataflow)

Nice to Have

• Knowledge of cloud platforms, such as:
• AWS services (e.g., S3, EMR), or equivalent offerings from other cloud providers
• Experience with scientific or statistical computation, especially related to online experimentation
• Experience with feature stores, such as Chronon
• Familiarity with AI coding assistants such as Claude Code and GitHub Copilot

Sample Projects & Areas of Impact: Data Pipelines & Evaluation Systems

Sample Projects & Areas of Impact

• Counterfactual evaluation:
• Support ad hoc metrics analysis
• Support pipeline debugging
• Support pipeline data migration
• Offline counterfactual scoring support pipeline migration
• Search simulator support pipeline migration
• Offline interaction detection support pipeline migration

Monitoring, Quality & Reliability: Holdout:

Monitoring, Quality & Reliability

• Implement comprehensive monitoring for traffic and models
• Clean up old data pipelines and deprecated tables, with appropriate testing
• Set up dashboards and monitoring for new and existing applications
• Set up alerting for new and existing applications using Grafana and PagerDuty