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Our First Netflix Data Engineering Summit

The Netflix TechBlog

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community! In this video, Sr.

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1. Streamlining Membership Data Engineering at Netflix with Psyberg

The Netflix TechBlog

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. What is late-arriving data?

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A Recap of the Data Engineering Open Forum at Netflix

The Netflix TechBlog

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems. ETL workflows), as well as downstream (e.g.

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Chaos Data Engineering Manifesto: 5 Laws for Successful Failures

DZone

During every major election, the wave would crest and crash against our overwhelmed systems before receding, allowing us to assess the damage. It's midnight in the dim and cluttered office of The New York Times, currently serving as the "situation room." A powerful surge of traffic is inevitable.

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Introducing Impressions at Netflix

The Netflix TechBlog

It requires a state-of-the-art system that can track and process these impressions while maintaining a detailed history of each profiles exposure. This nuanced integration of data and technology empowers us to offer bespoke content recommendations.

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