Jobs / KAYAK
Staff Data Platform Engineer
KAYAK · Berlin, BE, Deutschland
Berlin, BE, DeutschlandExp: 7+ yrsOnsite
Remuneration
Not specified
Location
Berlin, BE, Deutschland
Visa sponsorship
Not specified
Job summary
The Staff Data Engineer shapes and operates a shared data platform supporting analytics, machine learning, business intelligence, and AI-driven experiences. The role leads platform initiatives and defines standards for streaming ingestion, lakehouse storage, schema governance, observability, and semantic-layer strategy, while addressing complex operational challenges. The platform uses technologies including Apache Iceberg, Parquet, Kubernetes, and Python.
Benefits
Work from almost anywhere for up to 20 days per yearCompany-paid therapy sessionsCompany-paid Headspace subscriptionCompany-wide week offNo-meeting FridaysPaid parental leavePaid volunteer timeProfessional development fundsLeadership developmentOn-demand e-learningTravel discountsSix weeks of paid vacation and a birthday day offFree lunch two days per weekPension contributionsPublic transportation subsidiesBike leasing program
Qualifications
- At least 7 years of data engineering experience, including senior- or staff-level work with domain-wide technical scope.
- Experience designing and operating large-scale lakehouse architectures using open table formats such as Apache Iceberg, Parquet, and cloud object storage.
- Experience building and operating production streaming pipelines, including event-driven ingestion, exactly-once delivery, consumer lag management, checkpointing, recovery, and failure handling.
- Hands-on experience with data contracts, schema governance, metadata, or semantic-layer systems.
- Strong Python skills and experience writing maintainable, testable production code.
- Experience deploying and operating data workloads on Kubernetes, including containerized infrastructure, resource tuning, and health checks.
- Ability to influence multiple teams, communicate architectural trade-offs, and drive adoption.
- Experience mentoring engineers and improving technical standards through reviews, documentation, and reusable patterns.
- Comfort taking ownership of broad, ambiguous problem spaces.
- Experience with Trino, Apache Airflow, AWS or another public cloud provider, CI/CD automation, or Java is an advantage.
Responsibilities
- Design and evolve shared data platform architecture for streaming, lakehouse storage, schema management, semantic layers, and distributed queries.
- Lead platform initiatives from problem framing and architecture through implementation, rollout, and operational handoff.
- Define standards for data contracts, schema evolution, ingestion patterns, and production readiness.
- Create reusable patterns and reference architectures for ingestion, compaction, retention, schema governance, and observability.
- Establish platform monitoring, consumer lag tracking, data quality checks, and alerting.
- Collaborate with Operations, Security, Engineering, Data Engineering, and Product teams.
- Drive semantic-layer and metadata strategies for trusted self-service analytics and AI-driven data access.
- Evaluate streaming, storage, query, orchestration, and cloud technologies, balancing scalability, cost, complexity, and maintainability.
- Coach and mentor engineers through design reviews, code reviews, pairing, and technical guidance.
- Resolve complex platform challenges involving failure recovery, schema drift, partition management, and performance degradation.
Skills
AirflowAWSGitHubGitHub ActionsJavaKubernetesMakePythonTrino
Languages
PythonJava
Work schedule
Berlin office attendance 3 days per week
Industry
Travel
Relocation
No