About this role
Data Platform Engineer
Location: Tel Aviv, Israel
Description
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We’re growing and looking to hire a Data Platform Engineer,who embodies our core values: People First, Customer Obsession, Strive for Excellence, and Integrity.
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Claroty is a global leader in cyber-physical systems (CPS) protection, dedicated to securing the critical infrastructure that keeps the world running. We’re a fast-growing, award-winning team where innovation meets purpose—and we want you to help us define the future of cybersecurity.
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At Claroty, our technology strategy is focused on solving real-world cyber-physical security problems at scale through robust, distributed, cloud-native architectures. We design and evolve a unified platform that serves as the technological backbone for all Claroty products, delivering deep visibility across CPS environments—without disrupting critical operations. Our architecture emphasizes scalability, resilience, and extensibility to support both cloud and on-prem deployments.
About the Role
As a Data Platform Engineer, you will design, evolve, and scale our core data infrastructure and distributed pipelines, serving as the critical backbone that powers real-time analytics, AI research, and mission-critical cyber-physical protection across the Claroty platform.
Requirements
As a Data Platform Engineer, your impact will be:
- Platform Modernization: Shape and develop the core technology of our Data Platform, moving from design to implementation to support AI research and business intelligence.
- Scalable Pipeline Engineering: Design and build complex, distributed data pipelines that ingest, manipulate, and move data from a wide variety of sources at massive scale.
- Software Excellence: Build and maintain high-performance microservices and APIs that interface with our data ecosystem, ensuring low-latency and high reliability.
- Data Reliability: Implement best practices for data management, quality assurance, and security within our ecosystem.
- Cross-Functional Collaboration: Partner closely with Software Engineering, AI Research, DBAs, and Product Management to transform abstract data needs into real-world customer value.
- ML & AI Enablement: Integrate and manage robust data flows that directly power our ML and LLM pipelines in production environments.
- Leverage AI tools and capabilities to streamline daily work, routine tasks, and personal productivity.