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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager, Data Platform - **Company:** KAYAK - **Location:** Berlin, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Data Analysis, Business Logic, Computing Platforms, Big Data, Data Architecture, Information Engineering, Data Infrastructure, Data Retention, Data Sharing, Python (Programming Language), Machine Learning, Metadata, Raw Data, SQL Databases, Data Streaming, System Availability, Kubernetes, Apache Flink, Apache Kafka, Legacy Systems - **Published:** July 24, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=f416c7d0138624a4 ## About the Role * You have 8+ years of experience in data engineering, platform engineering, data architecture, or a related role. * You have meaningful people-management experience and a high technical bar. * You have strong knowledge of large-scale data platform architecture, including streaming, batch, storage, orchestration, and distributed query engines. * You have hands-on experience with technologies relevant to KAYAK's stack, such as Kafka, Flink, Iceberg, Trino, AWS, Kubernetes, Airflow, Python, SQL, and schema-based data contracts. * You have led platforms with high-throughput event streams and large-scale analytical data. * You have led platform migrations or infrastructure modernization efforts with strong judgment on risk, reliability, cost, and business continuity. * You are comfortable working across Engineering, Data Science, Data Engineering, Operations, Security, and Product on technically complex topics. * You bring high ownership, sound judgment, systems thinking, and the ability to influence senior stakeholders. ## Description KAYAK is seeking an Engineering Manager to lead the development and evolution of its shared data platform in a hands-on technical leadership role. This is a senior, hands-on leadership role. You will lead a Berlin-based team, set technical direction, make key architecture decisions, and get directly involved in the hardest platform and reliability problems. The team owns shared data infrastructure and raw data quality foundations, including ingestion, storage, orchestration, runtime, and platform governance. You will work closely with Engineering, Data Science, Data Engineering, Operations, Security, and Product partners to build a scalable, trusted, and cost-effective platform for analytics, reporting, experimentation, and machine learning., * Lead and develop a high-performing Berlin-based team of data platform engineers. * Evolve the platform architecture across ingestion, storage, orchestration, runtime, and lakehouse foundations. * Build core capabilities such as schema registry, data contracts, observability, metadata, and semantic layer implementation. * Enforce data retention policies and platform controls for different data types and usage needs. * Improve platform reliability by building the tooling and platform capabilities needed for monitoring, alerting, incident response, and operational readiness. * Drive platform modernization and simplify legacy systems where it creates clear value. * Define clear ownership boundaries so the platform team owns shared infrastructure and raw data quality, while downstream teams own business logic. ## Related Videos - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [7 Most Popular Web Developer Jobs in Europe](https://www.wearedevelopers.com/magazine/163-7-most-popular-web-developer-jobs-in-europe) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers)