> Markdown version of [/jobs/ext/1143953-data-engineer-iii](https://www.wearedevelopers.com/jobs/ext/1143953-data-engineer-iii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer III - **Company:** Expedia Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $146,000.0 - $233,500.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Java (Programming Language), Artificial Intelligence, Airflow, Amazon S3, Data Analysis, Cloud Computing, Code Review, Information Engineering, Data Security, Data Systems, Cursor (Graphical User Interface Elements), Database Queries, Software Debugging, Software Design Patterns, Distributed Computing Environment, Apache Hive, Python (Programming Language), Operational Databases, Software Tools, Cloud Services, Cloudera, Software Engineering, SQL Databases, Data Ingestion, Sql Optimization, Apache Spark, Jupyter, Information Technology, AWS Glue, Apache Kafka, Data Management, Virtual Agents, Data Pipelines, Databricks - **Published:** July 2, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=e4db27c4a07cdc78 ## About the Role * Bachelor's degree in Computer Science, Engineering, or a related technical field; or equivalent related professional experience. * 5+ years of relevant professional experience in data engineering, software engineering, or a closely related technical field. * Strong SQL skills and hands-on experience building and operating production-grade data pipelines or data products in cloud-based environments. * Experience with data modeling, schema design, and modern data access patterns, with the ability to make sound technical decisions within project scope. * Experience testing, monitoring, debugging, and improving data systems for reliability, observability, and operational quality., * Experience supporting analytics, business intelligence, experimentation, or AI/ML-oriented data use cases. * Experience with schema evolution, backfills, data freshness expectations, and service-level thinking for production data systems. * Experience leading moderately complex technical designs and driving delivery across multiple collaborators or dependent teams. * Experience improving engineering standards through mentoring, code reviews, documentation, and sharing best practices with peers. * Familiarity with cloud-native data tooling and distributed data processing patterns at scale. * Hands-on experience with technologies and infrastructure commonly used for end-to-end data engineering at Expedia, such as SQL, Python or Java, Spark, Hive, Trino, Querybook, Airflow, Jupyter, Databricks, AWS S3, AWS Glue Catalog, Unity Catalog, Dataproc, EGMP, Kafka Connect, DataPull, and Data Workbench. * Practical experience using AI-assisted engineering tools such as Claude, Codex, Glean, Cursor, or similar tools to accelerate development, troubleshooting, documentation, and knowledge discovery. * Ability to apply AI tools thoughtfully to enhance and automate data engineering workflows while maintaining strong standards for data quality, security, governance, and operational reliability., Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success. ## Description As a Data Engineer III in the AI and Analytics Platform team, you will design and improve reliable data pipelines, shape well-modeled data products, and help build analytics-friendly and AI-ready datasets that power self-service insights, automation, and emerging Agentic AI use cases across Expedia Group. This role is a strong fit for someone who enjoys solving complex data problems, writing high-quality code and SQL, and building systems that are scalable, observable, and trusted by their users. In this role, you will * Design, build, and maintain scalable batch and near real-time data pipelines and data products that support analytics, reporting, and downstream business use cases. * Help build foundational analytics- and AI-friendly datasets across domains so data is easier to discover, trust, reuse, and apply in reporting, decision-making, automation, and emerging AI use cases. * Write efficient, maintainable code and advanced SQL, applying strong engineering fundamentals to data ingestion, transformation, modeling, and access patterns. * Lead complex, well-defined projects from technical design through delivery, while identifying inefficiencies in existing systems and improving reliability, scale, and maintainability. * Build and improve data models, schema design patterns, and data quality practices so that data is easier to understand, trust, and use. * Strengthen operational excellence through testing, monitoring, alerting, troubleshooting, and clear ownership of service health, freshness, and performance expectations. * Partner closely with Product Managers, engineers, analysts, and business stakeholders to translate intake requests and business needs into practical technical solutions, with many projects and data products ultimately consumed by executive leadership for decision-making and visibility. * Mentor more junior engineers through collaboration, technical guidance, and code review. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [Kubernetes dev is fun, but setup and ops isn't! 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