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Senior Data Engineer

Nebius·Tel Aviv, Израиль·en
Не указаноПолная занятостьData EngineeringAI InfrastructureData InfrastructureEnterprise Software

Lead the design, implementation, and operation of reliable production data pipelines for analytics and machine learning. This hands-on role uses Python, SQL, workflow orchestration, cloud infrastructure, Docker, and Kubernetes, with a focus on resilient and cost-efficient data processing.

Обязанности

  • Design, build, and own production-grade data pipelines using Python and SQL
  • Develop resilient, stateless, and idempotent pipelines that handle retries, failures, and infrastructure interruptions
  • Implement data transformations, validation, and data quality checks
  • Optimize pipelines for performance, reliability, and cost efficiency
  • Collaborate with analytics, data science, and machine learning teams to deliver trusted datasets
  • Orchestrate pipelines with Airflow or an equivalent workflow framework
  • Package and run workloads with Docker on Kubernetes
  • Build CI/CD automation for data pipelines
  • Use infrastructure as code to manage pipeline runtime infrastructure

Требования

  • At least 8 years of experience as a data engineer, primarily focused on data pipelines
  • At least 6 years of hands-on Python and SQL experience
  • At least 3 years of experience running workloads on Kubernetes
  • Strong understanding of stateless system design and idempotent data processing
  • Experience building and operating data pipelines in cloud environments
  • Experience with workflow orchestration frameworks
  • Strong Linux fundamentals and production debugging skills
  • Working knowledge of spoken and written English

Будет плюсом

  • Open-source software experience
  • Apache Spark or similar distributed processing experience
  • Experience supporting machine learning workflows
  • Familiarity with Spot or preemptible compute
  • Experience with relational and non-relational data stores
  • Experience with large-scale or high-reliability data systems
  • Experience collaborating with data science and machine learning teams

Условия и преимущества

  • Competitive compensation
  • Career growth and learning opportunities
  • Flexibility and ownership
  • Collaborative and innovative culture
  • Opportunity to work on impactful AI projects
  • International work environment

Соответствие

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