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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, Technology - **Company:** Expedia Inc. - **Location:** Austin, TX, United States - **Experience:** Experienced - **Salary:** $231,000.0 - $323,500.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Computing, Continuous Integration, Customer Data Management, Data Architecture, Information Engineering, Extract Transform Load (ETL), Programming Tools, Distributed Computing Environment, Python (Programming Language), Machine Learning, Automation of Marketing, Operational Data Store, Software Engineering, SQL Databases, Systems Integration, Google Cloud, Large Language Models, Apache Spark, Eloqua, Technical Debt, Generative AI, Agentic-AI, Data Layers, Event Driven Architecture, Adobe, Infrastructure Automation Frameworks, Marketo, Data Management, Stream Processing, Data Pipelines, User Identification - **Published:** October 18, 2026 - **Apply:** https://www.dice.com/job-detail/ca825bb9-24c4-4db3-a3cf-ffb86249f5c2 ## About the Role * 10+ years of experience in data engineering, software engineering, platform engineering, or a related discipline, including 3+ years leading managers or multi-disciplinary engineering teams. * Experience defining and executing technology strategy across complex, enterprise-scale environments. * A track record of building and operating production-grade data platforms, pipelines, integrations, software services, and automation. * Strong knowledge of data architecture, data modeling, ETL/ELT, batch and streaming systems, APIs, event-driven design, orchestration, and distributed processing. * Experience with SQL, Python, cloud platforms such as AWS, Google Cloud Platform, or Azure, and technologies such as Spark, CI/CD, observability, and infrastructure automation. * Experience integrating CRM, marketing automation, customer data, analytics, experimentation, and personalization platforms. Experience with Salesforce Marketing Cloud, Adobe Marketo, Eloqua, or comparable platforms is a plus. * Experience establishing data quality, governance, security, privacy, reliability, responsible AI, and operational excellence practices. * Experience leading software delivery, production operations, incident management, modernization, and platform simplification. * Experience applying machine learning, generative AI, intelligent automation, or AI-enabled engineering practices in production or enterprise environments. * Strong communication and influencing skills, with the ability to translate complex technical concepts and trade-offs for technical and non-technical audiences. * A track record of building high-performing teams, developing leaders, and creating effective partnerships across functions. * Sound judgment in balancing innovation and speed with sustainability, control, maintainability, and long-term platform health. * Preferred qualifications * Experience with customer data platforms, identity resolution, consent management, audience activation, or personalization ecosystems. * Experience with machine learning, generative AI, predictive analytics, AI agents, model operations, LLM operations, experimentation platforms, or AI-enabled engineering productivity. * Familiarity with responsible AI practices, including evaluation, explainability, safety, human oversight, and lifecycle governance. * Experience designing data products, semantic layers, metrics platforms, or self-service analytics capabilities. * Experience leading cloud migration, platform consolidation, technology simplification, or other multi-year modernization programs. * Familiarity with GDPR, CCPA, or comparable privacy and data protection requirements. * Experience managing strategic technology vendors, external partners, and enterprise platform dependencies. * Experience working in a global, matrixed, consumer-facing, or high-volume digital environment. ## Description As the Director, Data Engineering, you will lead the Data Engineering, Software Engineering, AI, and Innovation capabilities supporting Expedia Group's Marketing Automation and MarTech 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, MarTech, 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. Leadership Approach: 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. In This Role You Will: * Set and execute a multi-year data and technology strategy aligned to Marketing Automation, MarTech, 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 MarTech 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, technology simplification, cloud and vendor cost management, and disciplined portfolio planning.