Idan Wenger
About Idan Wenger
Idan Wenger is a BI Team Lead at Augury, holding an MBA from The Open University of Israel and a B.A. in Information Systems and Economics from the University of Haifa. With extensive experience in business intelligence, he has successfully led data architecture transitions and manages numerous ETL pipelines and dashboards.
Work at Augury
Idan Wenger has been serving as the BI Team Lead at Augury since 2021. In this role, he manages over 250 ETL pipelines using Rivery, focusing on data accuracy and efficiency. He oversees the analytics platform management, which includes maintaining 350 dashboards on Sisense that serve 200 users. His responsibilities include ensuring that the data infrastructure supports the organization's analytical needs effectively.
Previous Experience in Business Intelligence
Prior to his current position, Idan Wenger worked at LivePerson as a BI Specialist from 2014 to 2021. During his tenure, he successfully led the transition to a new data architecture and pipelines, achieving an 80% reduction in processing time for ETL processes. He also held the position of BI Project Manager at Datacube from 2011 to 2014 and worked as a BI Leader at Healarium Inc. from 2012 to 2014.
Education and Expertise
Idan Wenger holds a Master of Business Administration (MBA) from The Open University of Israel. He also earned a Bachelor of Arts degree in Information Systems and Economics from the University of Haifa. His educational background supports his expertise in business intelligence and data management.
Training and Development Initiatives
In his role, Idan Wenger conducts ongoing training for data analysts to foster a culture of continuous learning and data-driven decision-making within the organization. This initiative highlights his commitment to professional development and the enhancement of analytical skills among team members.
Data Management Achievements
Throughout his career, Idan Wenger has implemented significant improvements in data management processes. Notably, he restructured BigQuery tables, resulting in a 20% reduction in analysis costs. His efforts contribute to increased efficiency and cost-effectiveness in data operations.