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Karabiben
Senior Data Engineer at Zendesk
Mahdi Karabiben is a seasoned data professional with extensive experience in data engineering and data platforms. He served as a Senior Data Engineer at Zendesk from November 2021 to October 2022, before being promoted to Staff Data Engineer, a position he held until October 2023. At Zendesk, Mahdi led initiatives in data quality, observability, and the development of core data platforms, focusing on areas such as data movement and transformation. He also played a pivotal role in enhancing Zendesk's data stack by introducing tools like dbt and automated data quality monitoring.14
Beyond his work at Zendesk, Mahdi is an author and speaker who shares insights on modern data technologies. He authored a liveProject series for Manning Publications, guiding learners through building end-to-end big data pipelines using tools like Apache Spark and Delta Lake.12 Currently, he works at Sifflet as a product and data leader.13
Mahdi holds an engineering degree in Computer Software Engineering from the National Institute of Applied Science and Technology, graduating with honors. He is also certified as a CCA Spark and Hadoop Developer and has completed leadership programs such as ESSEC's "Leading with Data-Driven Strategies & Analytics".1
Highlights
This chart from dbt Labs' State of Analytics Engineering report is actually uplifting.
Today, the biggest two challenges that data teams face (poor data quality and ambiguous ownership) are mostly related to people and processes rather than technical complexity or the data platform itself. This is a big shift from the struggles of the pre-Modern-Data-Stack world.
As someone who started working on data platforms during the Hadoop era, it's inspiring to see the industry move past spending endless engineering resources on maintaining complex data infrastructure that had a terrible return on investment.
In a way, this is a direct acknowledgment of the Modern Data Stack’s role in solving one of the Hadoop era’s biggest problems: today’s data platform (mostly) just works. Gone are the days of wasting expensive engineering time on building and maintaining the platform.
The Modern Data Stack may be dead, but for all its flaws, it solved the data platform’s technical hurdles. Now it’s time to solve the business ones.
#dataengineering #moderndatastack #dbt
