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 197

Data Engineering Engineering Entertainment Big Data 197

The Netflix TechBlog

FEBRUARY 14, 2025

Analytical Insights Additionally, impression history offers insightful information for addressing a number of platform-related analytics queries. The Flink jobs sink is equipped with a data mesh connector, as detailed in our Data Mesh platform which has two outputs: Kafka and Iceberg.

Tuning 166

Tuning Latency Efficiency Storage 166

The Netflix TechBlog

MARCH 5, 2019

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. What will be the cost of rolling out the winning cell of an AB test to all users?

Infrastructure 185

Infrastructure Cloud Scalability AWS 185

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.

Best Practices 361

Best Practices Code Testing Data Engineering 361

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. These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines.

Network 154

Network Tuning AWS Traffic 154

The Netflix TechBlog

NOVEMBER 20, 2023

These challenges are currently addressed in suboptimal and less cost efficient ways by individual local teams to fulfill the needs, such as Lookback: This is a generic and simple approach that data engineers use to solve the data accuracy problem. Users configure the workflow to read the data in a window (e.g.

Processing 219

Processing Big Data Efficiency Engineering 219

All Things Distributed

OCTOBER 7, 2015

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. These solutions lack interactive data exploration and visualization capabilities, limiting most business users to canned reports and pre-selected queries.

Cloud 114

Cloud Big Data AWS Analytics 114