Director, Technology

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.

Expedia Group B2B connects partners across the travel industry to our leading technology, supply, and services - helping them deliver seamless travel experiences to their customers. From airlines and hotels to financial institutions and other travel platforms, we power smarter, faster, and more impactful travel solutions through the most connected marketplace in the world

As the Director, Data Engineering, you will lead the Data Engineering, Software Engineering, AI, and Innovation capabilities supporting Expedia Group’s Marketing Automation and Mar Tech organization. You will set the vision and execution strategy for the platforms, products, and services that connect customer, marketing, product, and operational data and enable responsible, scalable use of AI.

Reporting to the head of Digital Operations, you will ensure that data, software, and AI capabilities are trusted, secure, scalable, and easy to use. You will partner with Marketing, Mar Tech, Analytics, Product, Technology, and responsible AI stakeholders to improve customer engagement, campaign effectiveness, operational efficiency, and the speed at which the organization can bring new ideas to life.

You are strategic, outcome-oriented, technically credible, and comfortable operating across business and technology. You create clarity, make thoughtful decisions, hold teams accountable for reliability, responsible AI, and customer value, and develop an inclusive environment where people can do their best work. You are curious about what’s next while remaining pragmatic about risk, cost, scale, and trust.

• Set and execute a multi-year data and technology strategy aligned to Marketing Automation, Mar Tech, personalization, customer engagement, and Digital Operations priorities.
• Lead three interconnected capabilities: data engineering and platform ownership; software engineering and integration services; and AI, innovation, experimentation, and emerging technology.
• Define architecture standards and make pragmatic build, buy, partner, and platform decisions that balance speed, scale, reliability, security, and cost.
• Build and evolve scalable data pipelines, data products, APIs, integrations, services, workflow automation, and developer tooling across the Mar Tech ecosystem.
• Establish strong practices for data quality, observability, lineage, access, governance, privacy, security, service ownership, and incident response.
• Partner with Analytics and business stakeholders to create trusted metrics, semantic models, and self-service capabilities that support better decisions.
• Enable advanced analytics, experimentation, machine learning, generative AI, and intelligent automation through fit-for-purpose data and engineering foundations.
• Establish the foundations for AI adoption, including model and prompt evaluation, data readiness, monitoring, cost management, access controls, human oversight, and responsible AI guardrails.
• Lead an innovation portfolio from problem discovery and prototyping through evaluation, productionization, or intentional shutdown—ensuring successful experiments become supported and measurable products.
• Create alignment across stakeholders on roadmaps, priorities, dependencies, investment choices, risks, and trade-offs, and communicate progress clearly to senior leadership.
• Build, lead, and develop a high-performing organization of engineering leaders and individual contributors across data, software, and innovation.
• Establish an operating model that balances committed delivery, platform health, technical debt reduction, modernization, and responsible experimentation.
• Improve efficiency through automation, reusable platforms,…