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Lead Compute Platform Engineer

WHO WE ARE  Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain custom...

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zetaglobal berlin Source published Oct 4, 2026 Verified 1 day ago
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Overview

<p><strong>WHO WE ARE&nbsp;</strong></p> <p>Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to <a href="https://www.zetaglobal.com">www.zetaglobal.com</a>.</p> <p><strong><span data-contrast="auto">The Role</span></strong><span data-ccp-props="{}">&nbsp;</span></p> <p><span data-contrast="auto">As a Senior Compute Platform Engineer on the Data Platform team, you will be part of the group responsible for building and running the data infrastructure that powers Zeta's platform, including Zeta’s&nbsp;lakehouse&nbsp;platform. The Data Platform team delivers reliable, cost-efficient data processing that scales with growth — so engineers and analysts can focus on business problems instead of wrestling with infrastructure.</span><span data-ccp-props="{}">&nbsp;</span></p> <p><span data-contrast="auto">The Data Platform team&nbsp;empowers data scientists and data engineers through a Scala data warehouse framework designed for data modeling and the creation of type-safe and easily testable batch jobs. The team also orchestrates a compute environment that simplifies the execution of Spark jobs,&nbsp;facilitating&nbsp;the analysis of terabytes of data with ease and cost-effectiveness. The runtime

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