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Berlin Office · Berlin, Germany
Live, first seen by us 32 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Cost Centers › Technology › DataFrom the employer’s posting
Design and evolve the shared data platform architecture
Lead platform initiatives from design through rollout and handoff
Define data contract and schema standards across teams
Build observability: pipeline monitoring, consumer lag, data quality alerts
Drive the semantic layer and metadata strategy
Design and evolve the architecture of KAYAK’s shared Data Platform
Deliver high-impact platform initiatives end-to-end
Define and promote technical standards for data contracts, schema evolution, ingestion patterns
Establish reliable observability across the platform, including pipeline monitoring, consumer lag tracking, data quality checks, and alerting.
Drive the semantic layer and metadata strategy
From the employer’s posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 32
Similar jobs usually come down between day 6 and day 54.
From 10,845 similar postings that came down. Coming down is not always a hire.
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Open jobs by the week we first saw them, last 12 weeks.
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- 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. Benefits and Perks
- Hands-on experience with data contracts, data 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.
- 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).
- 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 (e.g. S3) - 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.
- Distributed query engines such as Trino. - Experience with Kafka, Flink, or comparable streaming technologies. - Workflow orchestration tools such as Apache Airflow.
- 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.
To stand out: - Distributed query engines such as Trino. - Experience with Kafka, Flink, or comparable streaming technologies.
- Experience with Kafka, Flink, or comparable streaming technologies. - Workflow orchestration tools such as Apache Airflow. - Experience with AWS or an equivalent public cloud provider.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
KAYAK, part of Booking Holdings (NASDAQ: BKNG), is a leading travel search engine. With billions of queries across our platforms, we help people find their perfect flight, stay, rental car and vacation package. We're also transforming business travel with a new corporate travel solution, KAYAK for Business.
As an employee of KAYAK, you will be part of a travel company that operates a portfolio of global metasearch brands including momondo, Cheapflights and HotelsCombined, among others. From start-up to industry leader, innovation is in our DNA and every employee has an opportunity to make their mark. Our focus is on building the best travel search engine leveraging AI and data to make it easier for everyone to experience the world.
We are looking for a Staff Data Platform 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.
If you enjoy turning ambiguity into clear technical direction and durable solutions, we’d love to hear from you.
This role will be required to work from our Berlin office 3 days per week.
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 Data Science, and Analytics 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 data platform, including failure recovery, schema drift, partition management, and performance degradation.
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 (e.g. S3)
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, data 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 code reviews, documentation, and reusable patterns.
Comfort taking ownership of broad, ambiguous problem spaces.
To stand out:
Distributed query engines such as Trino.
Experience with Kafka, Flink, or comparable streaming technologies.
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.
Work from (almost) anywhere for up to 20 days per year
Focus on mental health and well-being:
Company-paid therapy sessions through SpringHealth
Company-paid subscription to HeadSpace
Company-wide week off a year – the whole team fully recharges (and returns without a pile-up of work!)
No meeting Fridays
Paid parental leave
Paid volunteer time
Focus on your career growth:
Development Dollars
Leadership development
Access to thousands of on-demand e-learnings
Travel Discounts
Employee Resource Groups
6 weeks paid vacation + a day off for your birthday
Free lunch 2 days per week
Pension plan contributions
Public transportation subsidies
Bike leasing program
Monthly social events, Thursday happy hours, sports teams
An awesome office in Friedrichshain, Berlin
At KAYAK, we want everyone to have the space to grow, share ideas and do great work. That's why we're focused on hiring the best talent from all walks of life and experiences, supporting them well and making sure no one feels like they have to fit a mold to belong here.
Need any adjustments for the interview, application or on the job? No problem – just give us a heads-up. We've got you.
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Berlin, Germany
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