• Proven experience (3+ years) as a Data Engineer or in a similar data-focused engineering role, working with large-scale or complex datasets
• Strong skills in at least one programming language commonly used for data engineering (preferably Python, Java is also acceptable).
• Hands-on experience with data processing frameworks (e.g. Spark, Flink, Beam or similar) and SQL for working with relational and analytical databases.
• Practical experience designing, implementing, and operating Airflow DAGs(or similar workflow orchestration tools), including dependency management, scheduling, and observability.
• Experience building and operating ETL/ELT pipelines on modern data platforms (e.g. cloud data warehouses, data lakes, or lakehouses).
• Experience with stream processing and real-time data products (e.g. Kafka, Kinesis, or similar).
• Understanding of data modeling concepts (e.g. dimensional modeling, Data Vault, star/snowflake schemas) and how they support analytics and reporting.
• Familiarity with version control, testing, and CI/CD practices for data workflows, including automated validation and deployment of Airflow changes.
• Experience using AI-assisted engineering tools responsibly to improve productivity while maintaining strong standards for quality, privacy, and security.
• Ability to identify pragmatic opportunities to leverage AI in data engineering workflows, for example in data quality monitoring, anomaly detection, metadata enrichment, lineage insights, or incident investigation.
• Ability to communicate clearly with both technical and non-technical stakeholders, explaining trade-offs and data design decisions.
• Find solutions to difficult or complex issues by applying different skills and techniques like analytical thinking, lateral thinking, and logical reasoning
• Constructively improve existing ideas, plans and solutions by reviewing them in a critical yet constructive manner, initiating concrete improvements and articulating their rationale
• Continuous Quality and Process Improvement
• Identify opportunities for process, system and/or structural improvements, by applying an understanding of process flows and the methods that can be used to boost effectiveness and efficiency
• Deliver clear, well-structured, and meaningful information to a target audience by using suitable communication mediums and language tailored to the audience
• Achieve mutually agreeable solutions by staying adaptable, communicating ideas in clear coherent language and practicing active listening.

• Design, build, and operate data pipelines and Airflow workflows (DAGs) (batch and/or streaming) to ingest, transform, and deliver data from diverse sources into analytics and operational data stores.
• Develop and maintain data models (e.g. dimensional, vault, or other analytical models) that are consistent, well-documented, and optimised for downstream use cases.
• Ensure data quality and reliability end-to-end by implementing validation, monitoring, testing, and alerting across pipelines, Airflow workflows, and datasets, with clear SLOs and error budgets where applicable.
• Own the operational excellence of the workflows you develop, including on-call participation where relevant, incident triage, troubleshooting, and driving root-cause analysis and follow-ups to prevent regressions.
• Collaborate with cross-functional teams to understand data needs, translate them into technical solutions, and enable self-service access to data where appropriate.
• Operate and improve big data platforms and tooling, following modern data engineering best practices, version control, and CI/CD workflows.
• Manage data governance aspects within your scope: ownership of datasets, documentation, access control, and alignment with security and privacy requirements.
• Contribute to craft standards and frameworks, sharing best practices, improving shared Airflow patterns and libraries, and mentoring more junior engineers where relevant.

• Health insurance
• Prepaid medical subscription (Regina Maria)
• Life insurance
• Meal vouchers
• Learning wallet
• Travel benefit
• Annual vacation leave of 25 business days, pro rata with the working period
• Birthday day off
• Summer break (short Fridays during summer)
• Work from Abroad program (up to 20 days/year in EU)
• Floating days off
• 2 Volunteer days/ year
• Home office one-time bonus
• Bookster
• Linkedin learning platform
• Headspace
• Employee discounts (travel, gym, dental, vision)

Booking Holdings Center of Excellence is part of Booking Holdings, the world's leading provider of online travel and related services, with a rich heritage of digital innovation. The Center provides access to specialized and highly skilled talent, supports projects powered by new and emerging technologies, leverages industry best practices, and fosters collaboration opportunities across all of the Booking Holdings brands, including Booking.com, Priceline, Agoda, KAYAK and OpenTable.

If you are interested to find out more about the Booking Holdings Center of Excellence visit our website: www.bookingholdings-coe.com.

Booking Holdings (NASDAQ: BKNG) is the world’s leading provider of online travel and related services, provided to consumers and local partners in more than 220 countries and territories through five primary consumer facing brands: Booking.com, Priceline, Agoda, KAYAK and OpenTable. The mission of Booking Holdings is to make it easier for everyone to experience the world.