Staff Data Platform Engineer

Who you are

• 7+ years of professional experience in data engineering, with meaningful time spent at a senior or staff level with domain-wide technical scope
• Experience designing and operating lakehouse architectures at scale — including open table formats (e.g., Apache Iceberg), columnar storage (Parquet) and cloud object storage
• 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
• Hands-on experience with data contracts, schema governance, metadata, or semantic-layer systems
• Strong Python skills and a track record of writing maintainable, testable production code
• Experience deploying and operating data workloads on Kubernetes — including managing containerized infrastructure, resource tuning and health checks
• Proven ability to influence multiple teams, communicate architectural trade-offs, and drive adoption
• Experience mentoring engineers and raising technical standards through reviews, documentation, and reusable patterns
• Comfort taking ownership of broad, ambiguous problem spaces
• Distributed query engines such as Trino
• Workflow orchestration tools such as Apache Airflow
• Experience with AWS or an equivalent public cloud provider
• CI/CD and deployment automation (e.g., GitHub Actions)
• Working knowledge of Java or another JVM-based language, given the JVM-based nature of several frameworks in this domain
• If you enjoy turning ambiguity into clear technical direction and durable solutions, we’d love to hear from you

What the job involves

• We are looking for a Staff Data Engineer to join our Data Platform team
• Our team builds and operates the shared foundation that powers analytics, machine learning, business intelligence and AI-driven experiences across the entire company
• As a senior individual contributor, you will shape how we move, store, govern, and serve data at scale, enabling every downstream team to build faster and with greater confidence
• 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. Make thoughtful trade-offs between latency, correctness, cost, and long-term maintainability
• 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
• Lead high-impact platform initiatives from problem framing and architecture design through implementation, rollout, and operational handoff
• Develop reusable patterns and reference architectures for streaming ingestion, compaction, retention, schema governance, observability, and other recurring data engineering challenges
• Establish reliable observability across the platform, including pipeline monitoring, consumer lag tracking, data quality checks, and alerting
• Collaborate closely with Operations, Security, Engineering, Data Engineering, and Product to evolve the platform, build cross-functional support, and ensure the platform meets the needs of its users
• Drive the semantic layer and metadata strategy that supports consistent and trusted self-service analytics and AI-driven data access
• Evaluate technologies and approaches across streaming, storage, query, orchestration, and cloud infrastructure, balancing scalability, operational complexity, cost, and maintainability
• Coach and mentor engineers through design reviews, code reviews, pairing, and reusable technical guidance
• Own the most complex architectural and operational challenges on the platform, including failure recovery, schema drift, partition management, and performance degradation

Benefits

• Work flexibly: Our global flexible work policy lets our teams decide if they head into one of our offices or work from anywhere else
• Team-wide time off: Most of our team disconnects at the same time each year to recharge and reconnect
• Global volunteer week: Take VTO (Volunteer Time Off) to support the organizations and charitable efforts you believe in
• Wellness: We take care of each other - providing opportunities and spaces to live that work-life balance
• Resource groups: Our five ERGs are employee-led groups for underrepresented communities and their allies
• Career growth: We provide opportunities for our team to develop their skills – or learn new ones – on their own terms