Analytics Data Engineering Engineering Speed 
The Netflix TechBlog
JULY 15, 2021
Data Engineers of Netflix?—?Interview Interview with Kevin Wylie 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. Kevin, what drew you to data engineering?
All Things Distributed
NOVEMBER 15, 2016
They require teams of data engineers to spend months building complex data models and synthesizing the data before they can generate their first report. The cost and complexity to implement, scale, and use BI makes it difficult for most companies to make data analysis ubiquitous across their organizations.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
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. All these micro-services are currently operated in AWS cloud infrastructure.
The Netflix TechBlog
DECEMBER 3, 2022
Languages Over time, the extraction of data from Netflix’s source systems has grown to encompass a wider range of end-users, such as engineers, data scientists, analysts, marketers, and other stakeholders. A large number of our data users employ SparkSQL, pyspark, and Scala.
The Netflix TechBlog
NOVEMBER 20, 2023
It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. Users configure the workflow to read the data in a window (e.g. The window is set based on users’ domain knowledge so that users have a high confidence that the late arriving data will be included or will not matter (i.e.
The Netflix TechBlog
MAY 26, 2020
Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the Cloud Network Infrastructure to address the identified problems. As with any sustainable engineering design, focusing on simplicity is very important. And excellent logging is needed for debugging purposes and supportability.
All Things Distributed
OCTOBER 7, 2015
However, the data infrastructure to collect, store and process data is geared toward developers (e.g., In AWS’ quest to enable the best data storage options for engineers, we have built several innovative database solutions like Amazon RDS, Amazon RDS for Aurora, Amazon DynamoDB, and Amazon Redshift.
Expert insights. Personalized for you.
189 
Let's personalize your content