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Data Engineers of Netflix?—?Interview with Samuel Setegne

Netflix Tech

Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. What drew you to Netflix?

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How to Save Time and Money by Testing Spark Locally

Xebia

Data Engineers were tempted by the pressure of the moment to give up on testing all together. There was no need for generating your own data; just take a percentage of production data. In many cases, these tasks ended up on the shoulders of the Data Engineers themselves. Data Engineer burnouts.

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

Netflix Tech

Netflix’s engineering culture is predicated on Freedom & Responsibility, the idea that everyone (and every team) at Netflix is entrusted with a core responsibility and they are free to operate with freedom to satisfy their mission. Give us a holler if you are interested in a thought exchange.

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Article: Moving towards a Future of Testing in the Metaverse

InfoQ Culture Methods

In this article, Tariq King describes the metaverse concept, discusses its key engineering challenges and quality concerns, and then walks through recent technological advances in AI and software testing that are helping to mitigate these challenges.

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Article: How I Contributed as a Tester to a Machine Learning System: Opportunities, Challenges and Learnings

InfoQ Culture Methods

Have you ever wondered about systems based on machine learning? In those cases, testing takes a backseat. And even if testing is done, it’s done mostly by developers itself. A tester’s role is not clearly portrayed. Testers usually struggle to understand ML-based systems and explore what contributions they can make.