High Scalability

MARCH 30, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Try out their platform.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MAY 26, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Try out their platform.

Education 100

Education AWS Software Engineering Scalability 100

The Netflix TechBlog

JULY 21, 2022

More importantly, the low resource availability or “out of memory” scenario is one of the common reasons for crashes/kills. We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform.

Big Data 179

Big Data Cache Engineering Data Engineering 179

The Netflix TechBlog

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

The Netflix TechBlog

DECEMBER 21, 2020

Some of the optimizations are prerequisites for a high-performance data warehouse. Sometimes Data Engineers write downstream ETLs on ingested data to optimize the data/metadata layouts to make other ETL processes cheaper and faster. It decides what to do and when to do in response to an incoming event.

Storage 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

MAY 26, 2020

Network Availability: The expected continued growth of our ecosystem makes it difficult to understand our network bottlenecks and potential limits we may be reaching. These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines.

Network 150

Network Tuning AWS Big Data 150

Abhishek Tiwari

JULY 7, 2023

In the era of big data and complex data processing, data pipelines have emerged as a popular solution for managing and manipulating data. They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights.

Logistics 52

Logistics Transportation Scalability Data Engineering 52

All Things Distributed

OCTOBER 7, 2015

Today, I am excited to share with you a brand new service called Amazon QuickSight that aims to simplify the process of deriving insights from a wide variety of data sources in a fast and affordable manner. Big data challenges. Put simply, data is not always readily available and accessible to organizational end users.

Cloud 137

Cloud Big Data AWS Analytics 137

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 202

Java Scalability Traffic Architecture 202

All Things Distributed

NOVEMBER 15, 2016

Today, I am very happy to announce that QuickSight is now generally available in the N. When we announced QuickSight last year, we set out to help all customers—regardless of their technical skills—make sense out of their ever-growing data. Put simply, data is not always readily available and accessible to organizational end users.

Analytics 152

Analytics Availability Media Social Media 152

The Netflix TechBlog

SEPTEMBER 10, 2019

Instead of relying on engineers to productionize scientific contributions, we’ve made a strategic bet to build an architecture that enables data scientists to easily contribute. The two main challenges with this approach are establishing an easy contribution framework and handling Netflix’s scale of data.

Metrics 215

Metrics Architecture Infrastructure Innovation 215