Data Engineer (AI Cloud)

Location: Germany, Israel, the Netherlands, Prague, Czech Republic, Remote - Europe, or the United Kingdom. Applicants must be authorized to work in the country where they apply.

Company

Nebius builds a full-stack AI cloud platform covering data, model training, and production deployment, with infrastructure spanning compute, storage, networking, and applied AI.

What you will do

• Own the design, delivery, and operation of complex data pipelines, datasets, and data-platform components.
• Translate business and analytical requirements into scalable data models, reliable data products, and technical plans.
• Design and evolve data architecture, storage, processing, and orchestration patterns for large-scale workloads.
• Improve data quality, observability, lineage, alerting, and incident response for critical datasets and pipelines.
• Investigate production performance, reliability, and data-correctness issues while establishing reusable tools and automation.
• Collaborate with product and business stakeholders, contribute to technical direction, mentor engineers, and participate in on-call support.

Requirements

• 5+ years of experience in data engineering, backend engineering, or a related role, or equivalent production experience.
• Independent delivery and operation of complex data pipelines or data-platform capabilities.
• Strong Python and SQL skills, including maintainable production code and query optimization.
• Hands-on experience with Airflow, Prefect, Dagster, or similar workflow orchestration tools.
• Strong knowledge of data modeling, data contracts, data architectures, and storage systems.
• Experience with testing, monitoring, data-quality validation, debugging, alerting, incident resolution, and technical decision-making under ambiguity.

Nice to have

• Experience with real-time or event-driven data platforms and streaming technologies.
• Experience with Docker, Kubernetes, Terraform, or cloud-native services.
• Familiarity with data governance, access control, privacy, GDPR, SOC 2, and data observability tools such as Great Expectations.
• Experience with shared libraries, platform tooling, technical documentation, or engineering mentorship.

Culture & Benefits

• Competitive compensation and opportunities for career growth and learning.
• Flexibility, ownership, and the opportunity to work on impactful AI projects.
• Collaborative, innovative, and international working environment.
• Fast-moving culture focused on meaningful impact, trust, and continuous growth.

Hiring process

• Coding interviews are part of the hiring process.
• Proof of employment eligibility is required as a condition of hire.