Senior Data Engineer

Why work at Nebius Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field. Where we work Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with RD hubs across Europe, North America, and Israel. The team of over 800 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI RD team. We are hiring a Senior Data Engineer whose primary responsibility is building and owning data pipelines. This is a hands-on data engineering role, focused on designing, implementing, and maintaining reliable data flows for analytics and machine learning. Infrastructure, cloud, and Kubernetes are used only as tools to run pipelines reliably and cost-efficiently — this is not an SRE or platform engineering role. What You’ll Do Core Responsibilities (Primary Focus) · Design, build, and own production-grade data pipelines using Python and SQL. · Develop stateless, idempotent pipelines that are resilient to retries, failures, and infrastructure interruptions. · Implement data transformations, validation, and data quality checks. · Optimize pipelines for performance, reliability, and cost efficiency. · Collaborate closely with Analytics, Data Science, and ML teams to deliver trusted datasets. Supporting Infrastructure (Secondary Focus) · Orchestrate pipelines using a workflow orchestration framework (e.g., Airflow or equivalent). · Package and run data workloads using Docker and deploy them on Kubernetes. · Use autoscaling and Spot / Preemptible compute for efficient pipeline execution. · Build CI/CD automation for data pipelines. · Use Infrastructure as Code only to provision and manage the infrastructure required to run pipelines. Experience Skills · 8+ years of experience as a Data Engineer, primarily focused on building data pipelines. · 6+ years of hands-on experience with Python and SQL. · 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. Nice to Have · Experience contributing to or working extensively with open-source software. · Experience building data pipelines using Apache Spark or similar distributed processing frameworks. · Experience building data pipelines that support machine learning workflows. · Familiarity with cost-optimized data processing (e.g., Spot / Preemptible compute). · Experience with relational and non-relational data stores. · Experience working with large-scale or high-reliability data systems. · Experience collaborating with strong Data Science and ML teams. What we offer Competitive salary and comprehensive benefits package. Opportunities for professional growth within Nebius. Flexible working arrangements. A dynamic and collaborative work environment that values initiative and innovation. We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us! ... (truncated, view full listing at source)