Description

We’re growing and looking to hire a Data Engineer who embodies our core values: People First, Customer Obsession, Strive for Excellence, and Integrity.

We are looking for a Data Engineer with strong technical expertise and outstanding collaboration skills to join our dynamic Data Science and Analytics team. You will be instrumental in building and maintaining the data infrastructure that powers Claroty’s solutions and supports a growing team of data scientists tackling the challenges of cyber security.

This role demands a hands-on, proactive engineer who can work side-by-side with analysts, data scientists and product teams to design scalable solutions, ensure data reliability, and drive technical excellence in our AWS-native environment.

About Claroty

Claroty has redefined cyber-physical systems (CPS) protection with an unrivaled industry-centric platform built to secure mission-critical infrastructure. The Claroty Platform provides the deepest asset visibility and the broadest, built-for-CPS solution set in the market comprising exposure management, network protection, secure access, and threat detection – whether in the cloud with Claroty xDome or on-premise with Claroty Continuous Threat Detection (CTD). Backed by award-winning threat research and a breadth of technology alliances, The Claroty Platform enables organizations to effectively reduce CPS risk, with the fastest time-to-value and lower total cost of ownership. Our solutions are deployed by over 1,000 organizations at thousands of sites across all seven continents.

A Great Place to Work® certified company, Claroty is headquartered in New York City with employees across the Americas, Europe, Asia-Pacific, and Tel Aviv. The company is widely recognized as the industry leader in CPS protection, with backing from the world’s largest investment firms and industrial automation vendors, recognized by KLAS Research as Best in KLAS for Healthcare IoT Security five years in a row, and ranking on the Forbes Cloud 100 and Deloitte Technology Fast 500 multiple consecutive years.

Responsibilities

As a Data Engineer, Your impact will :

• Make a critical contribution to shaping and developing the core technology of our Data Platform used for AI research and business intelligence, from design to implementation.
• Design and build complex data pipelines to move and manipulate data from a wide variety of data sources.
• Closely collaborate with various teams, including Software Engineering, AI Engineering and Product Management .
• Integrate and manage multiple robust data flows.
• Develop efficient ETL processes using Spark (PySpark), Airflow, databricks or other modern frameworks.
• Implement best practices for data management, quality assurance, and security within the AWS ecosystem.
  
  

Requirements

• 3+ years of professional experience as a Data Engineer in cloud-native environments, ideally within high-growth SaaS or cybersecurity companies.
• Experience working in Spark (preferably PySpark), Python, and distributed data processing at scale.
• Strong proficiency in AWS cloud services (S3, Glue, RDS, Bedrock, etc.).
• Experience supporting ML and LLM pipelines in production environments.
• Strong SQL skills, hands on experience analyzing and improving query executions
• Proficient understanding of data modeling for high scale large volume data sets
  
  

Advantage

• Exposure to security data and cyber-physical systems and network analytics.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• Solid understanding of data governance, security best practices, and compliance in cloud environments.
• Familiarity with real-time data streaming tools (e.g., Kafka, Kinesis).