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?

Data Engineering 189

Data Engineering Engineering Entertainment Big Data 189

Adrian Cockcroft

FEBRUARY 13, 2023

STP213 Scaling global carbon footprint management — Blake Blackwell Persefoni Manager Data Engineering and Michael Floyd AWS Head of Sustainability Solutions. DOP315 Sustainability in the cloud with Rust and AWS Graviton  — Emil Lerch AWS Principal DevOps Specialist and Esteban Kuber AWS Principal Software Engineer.

AWS 64

AWS Energy Architecture Programming 64

The Netflix TechBlog

DECEMBER 3, 2022

A large number of our data users employ SparkSQL, pyspark, and Scala. A small but growing contingency of data scientists and analytics engineers use R, backed by the Sparklyr interface or other data processing tools, like Metaflow. It solidifies different recipes or repeatable templates for data extraction.

Best Practices 358

Best Practices Code Testing Data Engineering 358

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. Requirements There are multiple ways you can solve this problem and many technologies to choose from.

Network 150

Network Tuning AWS Big Data 150

All Things Distributed

OCTOBER 7, 2015

Over the last several years, AWS has delivered on a comprehensive set of services to help customers collect, store, and process their growing volume of data. While BI solutions have existed for decades, customers have told us that it takes an enormous amount of time, engineering effort, and money to bridge this gap.

Cloud 137

Cloud Big Data AWS Analytics 137

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.

Analytics 152

Analytics Availability Media Social Media 152