Principal Data & AI Engineer, Reporting and Insights

Principal Data & AI Engineer, Reporting and Insights 

Introduction to the Team:  

Our Technology team partners across Expedia Group to create innovative products, services, and tools that deliver high-quality experiences for travelers, partners, and employees. Our shared technology platform, powered by data and machine learning, enables secure, differentiated, and personalized experiences that build loyalty and improve traveler satisfaction. 

 
This role sits within the Strategic Operations and Execution organization in the CTO Office and leads the AI Reporting and Insights capability, helping leaders turn complex data into clear, decision-ready insights.  As the Principal Data Engineer, AI Reporting and Insights, you will define how Expedia Group transforms operational, portfolio, and performance data into trusted executive insights. You will bring together reporting strategy, data architecture, and AI-enabled delivery to improve decision-making, reduce manual work, and build a scalable reporting foundation across the organization. 

 
You will also help set the standard for responsible, high-quality AI-powered reporting by applying large language models, agentic AI workflows, and modern AI tooling to executive reporting and self-service insights. 

In this Role You Will:  

• Own the AI-powered reporting and insights strategy from data ingestion through executive delivery, creating a unified approach to dashboards, metrics, narratives, and self-service insight products. 

•  Lead the Data Integrations and Enablement Platform, including the reporting data architecture, pipelines, and infrastructure needed to support trusted, scalable reporting. 

• Integrate business intelligence, metrics, and AI-assisted reporting into a connected capability that improves quality, speed, and usability for leaders and teams. 

• Set technical and operational standards within CTO Office while inheriting the EG standards for reporting tools and platforms, including Tableau, Looker, and AI-native reporting solutions. 

• Design and implement LLM-powered reporting workflows, including prompt engineering, retrieval-augmented generation (RAG), and agentic pipelines, to automate narrative generation, surface anomalies, and deliver self-service insight products. 

• Evaluate, select, and integrate enterprise approved AI platforms such as Azure OpenAI, AWS Bedrock, Anthropic, or similar solutions, ensuring reliability, security, and cost efficiency in production use cases. 

• Establish governance standards for executive-facing AI outputs, including hallucination mitigation, validation, accuracy monitoring, and responsible AI practices. 

• Partner with senior leadership on the insights roadmap, investment priorities, and capability-building decisions that shape the future-state reporting model. 

• Provide technical leadership and coaching across the reporting ecosystem, helping teams adopt clear standards, stronger practices, and modern ways of working. 

Minimum qualifications: 

•  Bachelor's degree in Computer Science, Information Systems, Data Science, Business Intelligence, or a related technical field; or equivalent professional experience. 

• 10 years of experience in data, analytics, business intelligence, reporting, or related technical roles with a Masters, 12 years with a Bachelors, or equivalent professional experience. 

• Strong proficiency in Python and SQL for data engineering, pipeline development, analytics, and AI/ML integration. 

• 3+ years of hands-on experience building or deploying AI/ML or LLM-based applications, including prompt engineering, RAG architectures, or agentic workflows using frameworks such as LangChain, LlamaIndex, or equivalent tools. 

• 2+ years of experience with at least one enterprise AI platform, such as Azure OpenAI, AWS Bedrock, Google Vertex AI, or an equivalent platform. 

Preferred qualifications: 

• 5+ years of experience leading cross-functional data or analytics programs at a Principal level or equivalent scope. 

• Experience designing and operating agentic AI systems that generate reports, answer data questions, or monitor metrics with minimal human intervention. 

• Familiarity with natural language interfaces for analytics, including NL-to-SQL and conversational BI patterns for enterprise environments. 

• Understanding AI output governance, including evaluation frameworks, confidence scoring, escalation patterns, and risk management for executive reporting use cases. 

•  Experience with modern data platforms such as EG specific implementations of Spark and Flink on top of Iceberg.  Snowflake, Databricks, or Delta Lake. 

• Familiarity with real-time or event-driven data patterns for low-latency insight delivery. 

• Strong executive communication skills, with the ability to translate complex technical concepts into clear business outcomes. 

•  Working knowledge of responsible AI principles, including explainability, auditability, and trust in AI-generated summaries and recommendations.