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

About Claroty:   

Claroty is on a mission to secure cyber-physical systems across industrial, healthcare, commercial and public sector environments: the Extended Internet of Things (XIoT). The Claroty Platform integrates with customers’ existing infrastructure to provide a full range of controls for visibility, exposure management, network protection, threat detection, and secure access. Our solutions are deployed by over 1,000 organizations at thousands of sites across all seven continents.

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 cyber-physical systems protection, with backing from the world’s largest investment firms and industrial automation vendors, as well as recognition from KLAS Research as Best in KLAS for Healthcare IoT Security, the Deloitte Technology Fast 500, the Forbes Cloud 100, and the Fortune Cyber 60. 

About the Role:

We’re looking for a curious, detail-oriented, and hands-on BI Engineer to join our growing Business Applications team. In this role, you will lead Business intelligence initiative, maintain and develop the company Datawarehouse to support data-driven decisions across the company.

You’ll play a key role in developing our BI infrastructure, working with tools such as Databricks, Rivery, Tableau, through collaborating closely with stakeholders from Finance, Customer Services, and Business Operations. If you're excited about translating business needs into scalable data solutions and being the go-to person for everything BI – this one’s for you.

• Build and maintain end-to-end BI solutions – from data extraction and modeling to dashboard creation and insights delivery
• Own and develop reports and dashboards in Tableau (and other BI tools)
• Partner with cross-functional teams to understand reporting needs and translate them into effective data solutions
• Design and implement efficient ETL processes
• Manage data pipelines and contribute to the organization’s data lake/warehouse architecture
• Support and maintain high-quality, consistent, and reliable datasets
• Document data models, dashboards, and processes
• Drive a data-first mindset across departments by making data accessible, visual, and actionable