Über diese Senior Data Analyst (Hardware Automation) Stelle bei Nebius
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 Hardware Infrastructure Automation team at Nebius operates at the intersection of physical infrastructure and intelligent software systems. We build the data layer that drives automation and operational decisions for our global hardware fleet.
We are looking for a Senior Data Analyst who can work end-to-end — from data modelling and pipeline engineering to dashboards and business recommendations. You will be a full owner of analytical projects: defining the problem, building the solution, and driving adoption with stakeholders.
You will work closely with SWE, SRE, and frontend teams to surface insights that directly influence how we scale and automate our infrastructure. If you are equally comfortable writing Python and SQL as you are presenting findings to leadership, this role is for you.
Your responsibilities will include:
- End-to-end project ownership. Lead analytical projects independently from scoping and data modelling through to delivery and iteration. Define success metrics, manage timelines, and communicate progress without supervision.
- Data engineering. Build and maintain reliable data pipelines using Python and SQL. Validate sources, monitor data quality, improve freshness, and ensure models are well-documented and reusable by the team.
- Dashboard development. Design and implement dashboards that give SWE, SRE, and frontend teams clear visibility into fleet health, utilisation, capacity, and automation coverage. Own dashboard quality and iteratively improve based on user feedback.
- Infrastructure analytics. Analyse large-scale hardware telemetry and operational data to identify bottlenecks, anomalies, and optimisation opportunities. Translate complex infrastructure signals into clear, actionable recommendations.
- Automation insight. Support the team's automation roadmap by quantifying the impact of automation initiatives, identifying gaps in coverage, and modelling scenarios that inform prioritisation.
- Stakeholder collaboration. Work directly with HW RnD, IT Operations, DC Operations, Logistics, and other teams to clarify requirements, align on metrics, and present results in a way that supports engineering decisions — not just "interesting numbers".
- Analytical best practices. Raise the standard of analytical work in the team through documentation, metric definitions, code reviews, and mentoring less experienced colleagues where relevant.
We expect you to have:
- Significant experience as a Data Analyst, Senior Data Analyst, or in a similar role with strong technical ownership.
- Strong proficiency in Python and SQL — you write clean, production-quality code, not just scripts.
- Proven experience building and maintaining dashboards used by engineering or operations teams.
- Experience owning analytical projects end-to-end: from data modelling and pipeline development through to stakeholder delivery.
- Solid grounding in statistics and analytical thinking, including descriptive analytics, hypothesis testing, and regression fundamentals.
- Strong attention to data quality, including validating definitions, identifying inconsistencies, and implementing monitoring.
- Comfort working with large, complex, and sometimes ambiguous datasets — including telemetry, logs, or operational data.
- Ability to communicate technical findings clearly to non-technical audiences, including senior leadership.
- Strong problem-solving skills — you break down ambiguous questions, form hypotheses, and identify practical next steps independently.
- Working knowledge of spoken and written English.
It will be an added bonus if you have:
- Experience with hardware infrastructure, data centre operations, or cloud infrastructure analytics.
- Familiarity with modern data stacks such as dbt, Airflow, BigQuery, Snowflake, or PostgreSQL.
- Experience with BI tools such as Tableau, Power BI, Looker, or Superset.
- Background in automation analytics, capacity planning, or fleet management.
- Experience mentoring other analysts or contributing to team standards and documentation.
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.
