Data Security Engineering Lead

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.

• Lead and own the organization’s data protection domain, including strategy, standards, and hands-on technical implementation
• Engineer, deploy, and continuously tune DLP policies across endpoints, email, SaaS, network proxies, and cloud platforms - covering both inline and API-based enforcement modes.
• Design and implement DSPM solutions to gain continuous visibility into sensitive data posture, data flows, misconfigurations, and exposure risks across cloud and multi-cloud environments.
• Drive data discovery initiatives to identify and inventory sensitive data across databases, SaaS applications, endpoints, and cloud storage.
• Define and implement data classification frameworks, labeling standards, and data handling policies integrated with DLP and DSPM controls.
• Build and maintain DLP detection rules, regular expressions, fingerprinting, and machine learning-based classifiers to minimize false positives and maximize coverage.
• Integrate DSPM findings into DLP enforcement workflows to create a closed-loop data protection architecture.
• Define and enforce data access governance, including least-privilege principles and monitoring of sensitive data access patterns.
• Monitor, triage, and investigate DLP alerts and DSPM-identified risks, collaborating with SOC and Security teams on escalation and remediation.
• Conduct risk assessments and identify gaps in data protection controls across systems, pipelines, and business processes.
• Support compliance and regulatory requirements (e.g., GDPR, ISO 27001, SOC 2) related to data security and privacy.
• Collaborate with Engineering, IT, Product, and GRC teams to embed data security controls into CI/CD pipelines, systems, and workflows.
• Maintain documentation, runbooks, and guidelines for DLP operations, DSPM posture management, and data security practices.

• 6+ years of experience in cyber security, with a strong focus on data security, data protection, or information security.
• Proven hands-on engineering experience with enterprise DLP platforms - including policy authoring, rule tuning, incident workflow configuration, and platform administration (e.g., Microsoft Purview DLP, Symantec DLP, Forcepoint, or equivalent).
• Hands-on experience deploying and operating DSPM tools (e.g., Cyera, Varonis, Rubrik Security Cloud, Normalyze, Securiti, or equivalent) to manage cloud data exposure and classification at scale.
• Deep understanding of DLP enforcement mechanisms: endpoint DLP, network DLP, email DLP, and cloud/API-based DLP controls.
• Strong experience with data discovery and classification across cloud environments (AWS, Azure, GCP), SaaS platforms, and on-premises systems.
• Ability to write and optimize detection logic - regular expressions, data fingerprinting, document fingerprinting, and EDM (Exact Data Matching).
• Experience integrating DLP and DSPM tools with SIEM, SOAR, and ticketing systems for alert routing and automated response.
• Experience securing data across cloud environments and SaaS platforms, including shadow IT and unmanaged data stores.
• Strong understanding of identity and access management and data access governance principles.
• Experience working cross-functionally with Security, IT, Engineering, Product, Privacy and GRC teams.
• Strong analytical mindset with the ability to communicate data security risks clearly to technical and non-technical stakeholders.
• Excellent written and verbal communication skills in English.
• Proactive, detail-oriented, and ownership-driven.

• 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