KAYAK, part of Booking Holdings (NASDAQ: BKNG), is the world's leading travel search engine. With billions of queries across our platforms, we help people find their perfect flight, stay, rental car and vacation package. We're also transforming business travel with a new corporate travel solution, KAYAK for Business.
As an employee of KAYAK, you will be part of a travel company that operates a portfolio of global metasearch brands including momondo, Cheapflights and HotelsCombined, among others. From start-up to industry leader, innovation is at our core and every employee has an opportunity to make their mark. Our focus is on building the best travel search engine to make it easier for everyone to experience the world.
We are looking for a Senior Data Engineer to join our Business Intelligence team.
Our team builds and operates the data backbone that serves as the single source of truth for the organization. We manage KAYAK’s business-critical reporting to support billing and provide the foundation for company-wide reporting and analytics.
If you want to build the systems that define how the business measures success, we’d love to hear from you.
This role will be required to work from our Berlin office 3 days per week.
Architect for scale: Develop and monitor robust data pipelines using Python, SQL, and Rundeck/Airflow that handle large-scale data volumes with high reliability.
Optimize performance: Design performant data models and optimize complex SQL queries for high-scale environments.
Ensure data reliability: build automated checks and alerts to catch errors early so financial and operational reports remain accurate.
Increase data access: automate repetitive tasks and build self-service tools to make data easier to use across teams.
Drive engineering excellence: experiment with and leverage AI-assisted coding tools to accelerate development cycles and enhance code quality.
Work with partners across the company: translate business questions into practical, maintainable technical solutions.
5+ years of proven experience in data engineering or analytics engineering within a related data-centric environment.
Experience owning end-to-end data pipelines (ingest → transform → test → monitor).
Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres).
Proficiency in Python and a software-engineering approach to building testable, maintainable code.
Experience with workflow orchestration and containerization (examples: Airflow, Docker).
Strong analytical and troubleshooting skills for investigating data issues.
Strong written and spoken English to communicate effectively across teams.
Stream processing or real-time systems (e.g., Kafka, Flink).
Modern BI tooling (e.g., Looker, Superset).
CI/CD and deployment automation (e.g., GitHub Actions).
Web frameworks for internal tools (e.g., Django, Flask).
Work from (almost) anywhere for up to 20 days per year
Focus on mental health and well-being:
Company-paid therapy sessions through SpringHealth
Company-paid subscription to HeadSpace
Company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
No meeting Fridays
Paid parental leave
Paid volunteer time
Focus on your career growth:
Development Dollars
Leadership development
Access to thousands of on-demand e-learnings
Travel Discounts
Employee Resource Groups
6 weeks paid vacation + a day off for your birthday
Free lunch 2 days per week
Pension plan contributions
Public transportation subsidies
Bike leasing program
Monthly social events, Thursday happy hours, sports teams
An awesome office in Friedrichshain, Berlin
At KAYAK, we want everyone to have the space to grow, share ideas and do great work. That’s why we’re focused on hiring the best talent from all walks of life and experiences, supporting them well and making sure no one feels like they have to fit a mold to belong here.
Need any adjustments for the interview, application or on the job? No problem - just give us a heads-up. We’ve got you.
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