Ensuring real-time data quality & democratization at Thinksurance
Ensuring data quality and governance across diverse data sources is one of the biggest challenges for modern data teams. Thinksurance faced this head-on, integrating structured and streaming data while maintaining real-time data quality and automated governance—all within a fully automated, continuously deployed data environment.
Hear from Cleber Barbado, Lead Data Architect, and Kevin Fischer, Principal Data Engineer at Thinksurance, as they share how they:
- Built an automated data quality framework with multiple validation layers before data reaches production
- Seamlessly integrated streaming and batch data to create a unified, real-time data ecosystem
- Leveraged Iceberg and Hive together to balance cost-efficiency and performance
- Used Starburst Galaxy’s federated query engine to power data democratization across teams
This session covers how Thinksurance architected a robust, scalable data ecosystem that eliminates manual intervention, ensures trusted data insights, and accelerates decision-making.
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Arne Ottens
Enterprise Solution Architect at Starburst

Cleber Barbado
Lead Data Team, Big Data Architect at Thinksurance

Korbi Zollner
Senior Manager Field Engineering at Starburst