Data Engineer

Kayak•Technology

Berlin Officeدوام كاملفي موقع العملالأسبوع الماضي

أنا مهتم بهذه الوظيفةمشاركة عبر واتساب

سجّل مجانًا – هذا ما يقدّمه لك الحساب

تصفّح أكثر من 1.200 وظيفة بمزايا مدعومة بمصدر
اطّلع على الدليل: اقتباس ومصدر لكل ميزة
احفظ الوظائف وتابع طلباتك
توصيات شخصية بحسب قيمك

سجّل الآن مجانًا

تحدّث أولًا مع رفيق – بلا نموذج ولا كلمة مرور

🔔 وظائف جديدة مثل هذه — مباشرة إلى بريدك

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💬 أو دع رفيق يبحث لك — مستشارك المهني المجاني ←

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.

KAYAK is looking for a Data Engineer to build the trusted data foundation behind machine learning across the company.

You’ll partner with data scientists to understand their modeling needs and what the available data can (and can’t) support.

You’ll transform large-scale raw data into production-ready datasets and build the scalable pipelines that make them dependable and reusable.

Working across Data Science, Data Engineering, and Data Platform, you’ll help address data gaps and bring new machine-learning use cases into production.

If you’re excited to shape how teams across KAYAK use data to build and scale machine learning, we’d love to hear from you.

This role will be required to work from our Berlin office 3 days per week.

In this role, you will:

Partner with the Data Science teams and help translate modeling needs into dataset requirements, then collaborate with Data Engineering and Data Platform to extend foundational pipelines into ML-ready datasets.

Design scalable and efficient dataset workflows and ensure pipeline reliability through validation, monitoring, and alerting; diagnose and resolve issues.

Ship production-ready data solutions that enable ML applications and deliver real-world impact on user experience and key business metrics.

Identify gaps and opportunities, contributing to technical decisions and roadmap priorities that strengthen the data foundation for current and future ML use cases.

Collaborate across Data Science, Engineering, and Data Platform, communicating technical decisions, findings, and trade-offs clearly and concisely to technical and non-technical audiences.

Please apply if you have:

Strong technical foundations in data engineering, software engineering, and systems design, backed by a track record of building and operating reliable, large-scale data pipelines. Demonstrated capability matters more than academic credentials.

Hands-on experience developing production data pipelines, with the ability to clearly explain the problems addressed, your specific contributions, and the resulting impact.

Ownership, sound judgment, and systems thinking, with the ability to navigate technical, reliability, cost, and risk trade-offs while working independently and recognizing when to seek guidance.

Fluency with AI-assisted workflows, leveraging modern tools to improve productivity and quality while critically evaluating their outputs and limitations.

Curiosity, humility, and a collaborative mindset, with a commitment to continuous learning, sharing knowledge, and improving together.

Bonus qualifications

Hands-on experience with technologies relevant to KAYAK’s stack, such as Kafka, Flink, Iceberg, Trino, AWS, Kubernetes, Airflow, Python, SQL, and schema-based data contracts.

Experience with feature stores or feature pipelines.

Familiarity with Agile ways of working, such as sprint planning and team ceremonies.

🎁Benefits

and Perks:

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

Inclusion

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.