ML-Ready Data Engineer — Berlin, Remote-Friendly

KAYAK; Berlin (MD); Hybrid; USD 84,000 - 124,000; Full time

Benefits offered by this job

Work from (almost) anywhere for up to

Mental health benefits

No meeting Fridays

Paid parental leave

Paid volunteer time

Development Dollars

Leadership development

On-demand e-learning access

Travel Discounts

6 weeks paid vacation + bday

Free lunch 2 days per week

Pension plan contributions

Public transportation subsidies

Bike leasing program

Monthly social events

Job summary

KAYAK is seeking a Data Engineer to build the trusted data foundation for machine learning across the company. You will transform large-scale raw data into production-ready datasets and create scalable pipelines used by Data Science, Data Engineering, and Data Platform teams.

The role requires collaboration across teams and will be based in Berlin with 3 days per week in the office. You will contribute to ML use cases and help address data gaps to improve user experience and business metrics.

Qualifications

• Strong foundations in data engineering, software engineering and systems design.
• Hands-on experience building production data pipelines.
• Ability to explain problems, contributions and impact clearly.
• Familiarity with AI-assisted workflows and evaluation of outputs.

Responsibilities

• Collaborate with Data Science to translate modeling needs into dataset requirements.
• Design scalable dataset workflows and ensure pipeline reliability through validation and monitoring.
• Ship production-ready data solutions enabling ML applications and business impact.
• Identify gaps and opportunities, influencing data platform roadmaps.
• Communicate decisions and trade-offs clearly across teams.

Skills

Data engineering

Software engineering

Systems design

Python

SQL

Tools

Kafka

Flink

Iceberg

Trino

AWS

Kubernetes

Airflow

schema-based data contracts

Job description

KAYAK is seeking a Data Engineer to build the trusted data foundation for machine learning across the company. You will transform large-scale raw data into production-ready datasets and create scalable pipelines used by Data Science, Data Engineering, and Data Platform teams.

The role requires collaboration across teams and will be based in Berlin with 3 days per week in the office. You will contribute to ML use cases and help address data gaps to improve user experience and business metrics.