Data Engineer (Machine Learning)

Location: Berlin office, hybrid; required to work from the Berlin office 3 days per week.

Company

hirify.global is a travel search engine and part of Booking Holdings, operating global metasearch brands and a corporate travel solution.

What you will do

• Partner with Data Science to translate modeling needs into dataset requirements and collaborate with Data Engineering and Data Platform on ML-ready datasets.
• Design scalable dataset workflows and maintain pipeline reliability through validation, monitoring, and alerting.
• Diagnose and resolve data pipeline issues.
• Deliver production-ready data solutions supporting machine-learning applications and business impact.
• Identify data gaps and opportunities while contributing to technical decisions and roadmap priorities.
• Communicate technical decisions, findings, and trade-offs across technical and non-technical teams.

Requirements

• Strong foundations in data engineering, software engineering, and systems design, with experience building and operating reliable, large-scale data pipelines.
• Hands-on experience developing production data pipelines, including the ability to explain the problems addressed, personal contributions, and resulting impact.
• Ownership, sound judgment, and systems thinking when balancing technical, reliability, cost, and risk trade-offs.
• Ability to work independently and recognize when to seek guidance.
• Fluency with AI-assisted workflows and the ability to critically evaluate their outputs and limitations.
• Curiosity, humility, collaboration, continuous learning, knowledge sharing, and a commitment to improvement.

Nice to have

• Hands-on experience with Kafka, Flink, Iceberg, Trino, AWS, Kubernetes, Airflow, Python, SQL, and schema-based data contracts.
• Experience with feature stores or feature pipelines.
• Familiarity with Agile practices such as sprint planning and team ceremonies.

Culture & Benefits

• Work from almost anywhere for up to 20 days per year.
• Company-paid therapy sessions, Headspace subscription, and a company-wide week off.
• No-meeting Fridays, paid parental leave, and paid volunteer time.
• Development dollars, leadership development, and access to on-demand e-learning.
• Six weeks of paid vacation, a birthday day off, travel discounts, pension contributions, and public transportation subsidies.
• Free lunch twice per week, bike leasing, social events, sports teams, and employee resource groups.