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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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Data Engineers of Netflix?—?Interview with Dhevi Rajendran

The Netflix TechBlog

Data Engineers of Netflix?—?Interview Interview with Dhevi Rajendran Dhevi Rajendran 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.

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Data Engineers of Netflix?—?Interview with Samuel Setegne

The Netflix TechBlog

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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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. past 3 hours or 10 days).

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Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

Now, imagine yourself in the role of a software engineer responsible for a micro-service which publishes data consumed by few critical customer facing services (e.g. You are about to make structural changes to the data and want to know who and what downstream to your service will be impacted.

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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 202
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Post: InterviewCamp.io, Scrapinghub, Fauna, Sisu, Educative, PA File Sight, Etleap, Triplebyte, Stream

High Scalability

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! this is going to be a challenging journey for any backend engineer! Triplebyte is unique because they're a team of engineers running their own centralized technical assessment.

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