Data Engineer II
Booking.com
Amsterdam Centrum, NH, NL
Onsite
2026-06-23
Estimated salary · Amsterdam
€47k–€75k
Low
€47K
Median
€60K
High
€75K
Market in Amsterdam · Eurostat SES 2025
Job description
Role Description:
**About Us:** At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world.
**Role Description**:
Within Growth Marketing, the Messaging \& Rewards area is responsible for delivering timely, relevant and measurable customer communications and incentives that help travelers discover, book, engage and return to Booking.com across the full customer lifecycle.
As a Data Engineer in this area, you will help build the data foundation that powers Messaging \& Rewards use cases across channels such as email, push notifications, in\-app messaging and emerging channels. Your work will focus on creating reliable, scalable and well\-governed data pipelines and datasets that enable audience creation, campaign performance measurement, funnel observability, customer engagement analysis, personalization and rewards effectiveness.
You will have the opportunity to work on foundational problems such as event logging, sent and engagement data coverage, cross\-channel attribution, pipeline reliability and the modeling of customer and messaging data needed to support both operational decision\-making and long\-term product and marketing strategy.
**Key Job Responsibilities and Duties:**
As a Data Engineer, you will be in charge of the development, performance, quality, and scaling of our data pipelines, focusing especially on data quality. You will work independently and will also be responsible for making technical decisions within a team.
* Rapidly developing next\-generation scalable, flexible, and high\-performance data pipelines.
* Solving issues with data and data pi