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

JUNE 1, 2021

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?

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

The Netflix TechBlog

NOVEMBER 14, 2023

By focusing solely on updates and avoiding reprocessing of data based on a fixed lookback window, both Stateless and Stateful Data Processing maintain a minimal change footprint. This approach ensures data processing is both efficient and accurate.

Tuning 244

Tuning Processing C++ Efficiency 244

Dynatrace

JULY 6, 2022

Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. Automating IT practices offers enterprises faster data centers and cloud operations, as well as increased flexibility and accuracy. IT automation tools can achieve enterprise-wide efficiency. Read eBook now!

Artificial Intelligence 191

Artificial Intelligence Tuning Strategy Big Data 191

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. In the Efficiency space, our data teams focus on transparency and optimization.

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

The Netflix TechBlog

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.

Analytics 207

Analytics C++ Innovation Engineering 207

The Netflix TechBlog

SEPTEMBER 18, 2020

Julie] Chris and I have the same primary stakeholders (or engineering team that we support): Encoding Technologies. They are continuously innovating compression algorithms to efficiently send high quality audio and video files to our customers over the internet. Tell me about some of the exciting projects you’re a part of.

Analytics 223

Analytics Education Innovation Engineering 223