Senior Data Platform Engineer (Data Lake and Catalog)

Overview

As a Senior Software Engineer on Expedia Group's Data Lake and Catalog team, you will shape the core of our Lakehouse and data discoverability capabilities. You’ll design, build, and operate scalable data platform services that help product and analytics teams find and trust data. You’ll mentor engineers, drive reliability and observability, and collaborate across teams to evolve our data infrastructure and open-source contributions. This is a hands-on role with impact on scale and developer experience.

Responsibilities

• Design, build, and evolve scalable, maintainable data lake platform software
• Lead by example with high engineering quality and well-tested code
• Promote an SLO-driven culture focusing on reliability, observability, and incident learnings
• Collaborate with engineers and stakeholders to clarify requirements and deliver effectively
• Break down complex problems into pragmatic technical solutions and plans
• Own services and platform capabilities through design, delivery, and production operation
• Lead technical design for scalable, resilient platform components
• Mentor engineers through guidance and collaboration
• Partner with architects and cross-functional teams to build broader solutions
• Stay current with tech trends to improve the platform and developer experience

Key requirements

• Senior software engineering experience building and operating production systems at scale
• Passion for technology, engineering excellence, and solving complex problems
• Experience delivering end-to-end solutions with focus on scalability, reliability, and observability
• Strong knowledge of JVM and server-side Kotlin/Java
• Solid understanding of Hadoop ecosystem (Spark, Hadoop, Hive)
• Experience with cloud platforms and data infrastructure, especially AWS (EMR, S3, Glue)
• Experience in Agile environments and code reviews
• Strong communication across technical and business stakeholders
• Ability to manage multiple priorities in a fast-paced environment
• Good understanding of architectural patterns and trade-offs

• strong communication
• cross-functional collaboration
• problem-solving mindset
• JVM-based Kotlin/Java
• Hadoop ecosystem (Spark, Hadoop, Hive)
• AWS cloud services (EMR, S3, Glue)