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Senior Data Engineer

Nebius· Technology
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Hybrid (Europe (Remote))Full-timePosted 7mo ago

About the role

Senior Data Engineer to build and operate Nebius's data platform, delivering complex data products end to end and enabling data-driven decision making across the organization.

Responsibilities

  • Own the design, delivery, and operation of complex data pipelines, datasets, and platform components.
  • Translate business and analytical requirements into scalable data models, reliable data products, and clear technical plans.
  • Design and evolve data architecture, storage, processing, and orchestration patterns for large-scale workloads.
  • Improve data quality, observability, lineage, and incident response for critical datasets and pipelines.
  • Investigate and resolve challenging performance, reliability, and data-correctness issues in production.
  • Establish reusable tools, conventions, and automation that improve engineering productivity and reduce operational risk.
  • Work with product teams and business stakeholders to define data contracts, priorities, and success criteria.
  • Contribute to technical direction through design reviews, thoughtful trade-offs, and documentation.
  • Support and mentor other engineers through reviews, pairing, and knowledge sharing.
  • Participate in the on-call rotation and take ownership of improving the operational health of the systems you support.

Qualifications

  • 5+ years of experience in data engineering, backend engineering, or a related role; or equivalent experience delivering and operating production data systems.
  • Proven experience independently delivering complex data pipelines or data-platform capabilities from problem definition through production operation.
  • Strong Python and SQL skills, including writing maintainable production code and optimizing non-trivial queries.
  • Hands-on experience with workflow orchestration tools such as Airflow, Prefect, or Dagster.
  • Strong understanding of data modeling, including designing maintainable analytical models and data contracts for multiple consumers.
  • Solid knowledge of data architectures and storage systems, including the trade-offs between different processing and storage approaches.
  • Experience designing for reliability: testing, monitoring, data-quality validation, alerting, debugging, and incident resolution.
  • Ability to make technical decisions under ambiguity, explain trade-offs clearly, and collaborate effectively with engineers and non-technical stakeholder

Skills

Required:PythonSQLData modelingWorkflow orchestration

Benefits

  • Competitive compensation
  • Career growth and learning opportunities
  • Flexibility and ownership
  • Collaborative and innovative culture
  • Opportunity to work on impactful AI projects
  • International environment and talented teams
Last updated Sep 9, 2026. Interested? Apply on the company site.
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