Senior Data Engineer

Nebius Group; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Career growth opportunities

Flexible work environment

Collaborative culture

Impactful AI projects

International teams

Job summary

Nebius is seeking a Senior Data Engineer to own significant parts of the data platform. You will transform ambiguous business needs into pragmatic data solutions, and enhance reliability, scalability, and usability of the data ecosystem across Nebius.

Collaborate with product, platform, and business teams to deliver trusted data products. You will work closely with engineers and stakeholders, shaping architecture and data contracts while mentoring peers and contributing to technical direction.

Qualifications

• 5+ years of experience in data engineering or backend data systems.
• Proven ability to deliver complex data pipelines from problem definition to production.
• Strong Python and SQL skills with production-quality code.
• Hands-on with workflow orchestration tools (Airflow/Prefect/Dagster).
• Strong data modeling, data contracts, and multiple consumer perspectives.
• Experience with data architectures and storage system trade-offs.
• Ability to make decisions under ambiguity and collaborate with engineers and stakeholders.

Responsibilities

• Own design, delivery, and operation of complex data pipelines and datasets.
• Translate business needs into scalable data models and data products.
• Design data architecture, storage, processing, and orchestration for large-scale workloads.
• Improve data quality, observability, lineage, and incident response.
• Resolve performance and reliability issues in production environments.
• Build reusable tooling, automation, and engineering standards.

Skills

Python

SQL

Data modeling

Data pipelines

Workflow orchestration

System reliability

Tools

Airflow

Prefect

Dagster

Docker

Kubernetes

Terraform

Job description

About Nebius:

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

The role

The Data Engineering team builds and operates the data platform that powers analytics, business intelligence, operational reporting, and data-driven products across Nebius. We ingest data from internal and external systems, develop reliable transformation pipelines and data models, and make trusted datasets available to business and product teams.

We are looking for a Senior Data Engineer to own substantial parts of our data platform and deliver complex data products end to end. You will turn ambiguous business needs into pragmatic technical solutions, make architecture and implementation trade-offs, and improve the reliability, scalability, and usability of our data ecosystem.

You will work closely with product, platform, and business teams, helping them use data effectively while ensuring that our systems remain maintainable and trustworthy as Nebius grows.

Your 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.

Must-haves:

• 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

Nice-to-haves:

• Experience with real-time or event-driven data platforms and streaming technologies.
• Experience building or operating cloud-native services with Docker and Kubernetes.
• Familiarity with Infrastructure as Code, particularly Terraform.
• Experience with data governance, access control, privacy, and compliance requirements such as GDPR or SOC 2.
• Experience with data observability and quality tools or frameworks, such as Great Expectations.
• Experience improving engineering standards through shared libraries, platform tooling, technical documentation, or mentoring.

We conduct coding interviews as part of the process.

Benefits & Perks:

• 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

What’s it like to work at Nebius:

Fast moving- Bold thinking- Constant growth- Meaningful impact- Trust and real ownership- Opportunity to shape the future of AI

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.

If you need accommodations during the application process, please let us know.