Data Engineer
Amsterdam, Noord-Holland · Booking.com · Booking.com
Omschrijving
Data Engineers are responsible for the development, performance, quality, and scaling of Booking’s data pipelines, with a special focus on data quality. The incumbent will take part in the execution of technical tasks within the scope of data management. As part of a team, the data engineer builds internal tools/infrastructure for other teams, or directly contributes to building user-facing products.
In this role, you will be expected to operate with independence across core architectural and deployment tasks, while applying hands-on experience in building reliable software and data solutions. You will also play a key role in advancing our "Data as a Product" mindset, ensuring our datasets are robust enough to power the next generation of autonomous and programmatic systems.
Key Responsibilities
Data Architecture & Modeling:
Independently segment data assets into sustainable and business-enabling domains.
Create physical data models to meet business requirements and map data flows between systems and workflows autonomously.
Support the definition of data architecture requirements and processing methodologies.
Data as a Product & Advanced Consumption:
Data as a Product: Design, build, and maintain well-managed, unified data solutions treated as standalone products.
AI & MCP Enablement: Engineer highly reliable, high-quality data assets to be leveraged not just for traditional BI dashboards, but optimized for programmatic consumption via Model Context Protocols (MCPs) and autonomous AI Agents.
Build extensible data pipelines spanning different data encodings to support these varied, advanced business requirements.
Data Solution Build & System Ownership:
Independently deploy code to production while maintaining end-to-end system ownership.
Implement scalable tooling for data flow automation, efficient data ingestion solutions, and batch/event-based streams.
Monitor relevant SLIs and SLOs, observability, application monitoring, and engineering for failure to ensure reliable solutions.
Data Quality & Governance:
Independently support the development and use of data validation solutions for values and schemas to guarantee data accuracy and reliability.
Implement and use solutions for monitoring, failure detection, and data availability to ensure data timeliness and completeness.
Ensure data solutions meet all regulatory, compliance, and risk management requirements by supporting the proper definition of processes and controls along data flows.
Software Engineering Best Practices:
Apply solid experience in writing and refactoring code, building tools, and managing project dependencies.
Adhere to core engineering principles (KISS, SOLID, DRY) and utilize technical documentation and test automation.
Requirements
Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
Proven independence in data architecture, physical data modeling, and deploying code to production.
Hands-on experience with SLIs/SLOs, test automation, and scalable data flow tooling.
Forward-thinking mindset with experience or strong interest in structuring data to power LLMs, MCPs, and agentic workflows.
Technical Requirements
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