Staff Data Platform Engineer

Join KAYAK as a Staff Data Platform Engineer, where you will shape the architecture of our shared Data Platform and drive high-impact platform initiatives. You will collaborate closely with various teams, establish reliable observability, and coach and mentor engineers. Enjoy flexible work options, team-wide time off, and opportunities for career growth.

Design and evolve the architecture of KAYAK’s shared Data Platform, including near-real-time streaming, lakehouse storage, schema management, semantic layer, and distributed query infrastructure.

If you enjoy turning ambiguity into clear technical direction and durable solutions, we’d love to hear from you

Responsibilities

• Deliver high-impact platform initiatives end-to-end — from problem framing and architecture design through implementation, rollout, and operational handoff.
• Define and promote technical standards for data contracts, schema evolution, ingestion patterns, and production readiness across platform and domain teams.
• Experience deploying and operating data workloads on Kubernetes — including managing containerized infrastructure, resource tuning and health checks
• Experience mentoring engineers and raising technical standards through reviews, documentation, and reusable patterns
• Experience building and operating streaming data pipelines — including event-driven ingestion, exactly-once delivery semantics, consumer lag management, checkpoint and recovery strategies, and failure handling in production environments
• Proven ability to influence multiple teams, communicate architectural trade-offs, and drive adoption

Requirements

• Experience designing and operating lakehouse architectures at scale — including open table formats (e.g., Apache Iceberg), columnar storage (Parquet) and cloud object storage
• Hands-on experience with data contracts, schema governance, metadata, or semantic-layer systems

Comfort taking ownership of broad, ambiguous problem spaces

• 7+ years of professional experience in data engineering, with meaningful time spent at a senior or staff level with domain-wide technical scope
• Strong Python skills and a track record of writing maintainable, testable production code

Distributed query engines such as Trino

• Experience with AWS or an equivalent public cloud provider
• Working knowledge of Java or another JVM-based language, given the JVM-based nature of several frameworks in this domain

Preferred

• Workflow orchestration tools such as Apache Airflow
• CI/CD and deployment automation (e.g., GitHub Actions)