The Netflix TechBlog

OCTOBER 28, 2021

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.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

The Netflix TechBlog

JANUARY 11, 2022

Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix, including how our platform investments support running tests at scale while enabling innovation. Curious to learn about what it’s like to be a Data Engineer at Netflix?

Innovation 243

Innovation Metrics Engineering Testing 243

The Netflix TechBlog

NOVEMBER 14, 2023

Data Load Type : The ETL can either load the missed/new data specifically or reload the entire specified range. This helps overwrite data only when required and minimizes unnecessary reprocessing. As seen above, by chaining these Psyberg workflows, we could automate the catchup for late-arriving data from hours 2 and 6.

Tuning 244

Tuning Processing C++ Efficiency 244

The Netflix TechBlog

MARCH 5, 2019

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. How can we automatically provision or de-provision access privileges?

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

Dynatrace

JULY 6, 2022

While automating IT practices can save administrators a lot of time, without AIOps, the system is only as intelligent as the humans who program it. This requires significant data engineering efforts, as well as work to build machine-learning models. Monitoring automation is ongoing. Digital process automation tools.

Artificial Intelligence 198

Artificial Intelligence Tuning Strategy Big Data 198

O'Reilly

FEBRUARY 18, 2020

Infrastructure and ops usage was the fastest growing sub-topic under the generic systems administration topic. DevOps aims to produce programmers who can work competently in each of the layers in a system “ stack.” The results for data-related topics are both predictable and—there’s no other way to put it—confusing.

Software Architecture 132

Software Architecture DevOps Data Engineering Architecture 132

The Netflix TechBlog

SEPTEMBER 10, 2019

Our data scientists faced numerous challenges in our previous infrastructure. Complex business logic was embedded directly into the ETL pipelines by data engineers. In order to replicate results, scientists had to delve deep into the data, code, and documentation. This is an ongoing journey.

Metrics 215

Metrics Architecture Infrastructure Innovation 215