Business Intelligence Developer

We are looking for a professional and enthusiastic BI Developer to join our expending team!

About Us

Perimeter 81, recently acquired by Check Point, is a networking and network security leader that aims to deliver the premier SASE platform in the market. We are redefining the way businesses connect in the age of cloud and remote work with an innovative approach that combines cloud and on-device protection. We have over 200 employees with offices in New York, Los Angeles and Tel Aviv offering a global and multicultural work environment. Perimeter 81 is growing fast and looking for extraordinary team members to help us support our fast-growing customer base of more than 3,000 customers, including leading businesses of all sizes and industries.

Major Responsibilities

As a BI Developer, you will be responsible for:

• Design, build, and maintain end-to-end easy-to-use data solutions. This includes orchestration, data modeling, visualization, monitoring, alerting, experimentation models, etc.
• Collaborate effectively with cross-department stakeholders to capture analytical requirements
• Develop high-level dashboards
• Analyze complex datasets, and provide useful actionable recommendations

Desired Background

• At least 3 years of Python practical experience.
• Full proficiency in SQL with at least 5 years of experience in manipulating large, complex, and semi-structured data sets
• Deep understanding of BI methodologies and data architecture principles
• Strong ability to interpret data, and understand business processes and challenges from a business unit’s perspective
• Experience with data visualization tools (Looker - advantage)
• Solid data visualization and storytelling skills
• Experience with columnar, distributed, and decoupled data warehouses (e.g Redshift, Snowflake, Bigquery, Vertica)
• BSc in Computer Science, Mathematics, Industrial Engineering, or equivalent academic knowledge.
• Excellent personal communication and relationship-building skills.
• Advantage - Experience in using statistical Python libraries such as pandas and Scikit-learn.