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# Data Analyst

- **Company:** Booking.com
- **Location:** Amsterdam, Netherlands
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Information Engineering, Data Infrastructure, Data Visualization, Python (Programming Language), SQL Databases, Tableau (Software), Data Analytics
- **Published:** October 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b5342fb8bd64d3ed

## About the Role

We're looking for a motivated and data-driven individual with strong attention to detail, who can translate business questions into practical analytical solutions and communicate insights clearly to diverse audiences., * 2-3 years of professional experience in a similar role

 * Driven and results-oriented personality.
 * Ability to translate business problems into analytical approaches.
 * Open to feedback and always looking for ways to improve performance.
 * Able to understand details while keeping an eye on the bigger picture.
 * Ability to work independently while seeking guidance for complex tasks.
 * A collaborative mindset and willingness to develop your technical skills.
 * Minimum of 2 years of experience in a data or software adjacent field, working with systems and data infrastructure at scale.
 * Proficiency in data analysis languages (e.g., SQL, Python) and visualization tools (e.g., Tableau).

## Description

The Partner Payments Analytics team is part of the FinTech Business Unit. As a Data Analyst I, you'll use data to understand and improve Booking.com partners' experience and help grow adoption of payment solutions. You'll partner with FinTech teams to define business problems, establish the right metrics and turn findings into clear, actionable recommendations., * Design and deliver parts of data analytics solutions based on business requirements.

 * Work independently on consuming data, preparing it for analytical use and translating business problems to data stories.
 * Driving the implementation of reliable and well trusted metrics defined by the business.
 * Ensuring quality of their own work by validating it through peer review.
 * Connecting with peers in related crafts (e.g. Data Engineering) as needed on specific projects to ensure successful outcomes.
 * Contribute to knowledge sharing and the wider Data Analytics community.