Data Engineer III

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.

Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Introduction to the team

We build the intelligence layer for Expedia Group’s advertising supply. Our systems forecast ad inventory, track delivery accuracy, and flag at‑risk campaigns across global markets. Advertisers use our forecasts to plan and book with confidence; Revenue Operations uses our risk signals to prevent under-delivery.

As a Data Engineer III on M&I Forecasting, you will own and scale the data foundations behind ad inventory forecasting. You’ll design, build, and operate pipelines, analytics layers, and impression data models that power forecast accuracy measurement, pacing analysis, and delivery risk detection across global markets. You’ll drive data quality, lineage, and observability, partnering with data science and engineering to improve forecast performance.

In this role, you will:

• Design, build, and enhance scalable, secure, and reliable data pipelines and services that enable analytics, experimentation, and product features across multiple business domains.
• Develop, optimize, and maintain batch and streaming data processing solutions, including data modeling, schema evolution, and API design to support downstream consumers and applications.
• Implement robust data quality, validation, monitoring, and observability practices to ensure accuracy, completeness, and timely availability of data for stakeholders.
• Collaborate with engineers, product managers, analysts, and data scientists to translate business and analytical requirements into well-architected data solutions and reusable components.
• Apply and extend engineering best practices for performance, reliability, and cost efficiency, including testing, CI/CD, deployment automation, and operational runbooks for data systems.