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 181

Data Engineering Engineering Big Data Software Engineering 181

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

Dynatrace

JULY 6, 2022

Developing automation takes time. This requires significant data engineering efforts, as well as work to build machine-learning models. This kind of automation can support key IT operations, such as infrastructure, digital processes, business processes, and big-data automation. Big data automation tools.

Artificial Intelligence 213

Artificial Intelligence Tuning Strategy Big Data 213

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 217

Analytics C++ Innovation Engineering 217

The Netflix TechBlog

SEPTEMBER 18, 2020

I bring my breadth of big data tools and technologies while Julie has been building statistical models for the past decade. Julie] Chris and I have the same primary stakeholders (or engineering team that we support): Encoding Technologies. My work is typically developed in R or Python. Do they cause less errors?

Analytics 231

Analytics Education Innovation Engineering 231

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 225

Infrastructure Big Data Transportation Architecture 225

All Things Distributed

OCTOBER 7, 2015

However, the data infrastructure to collect, store and process data is geared toward developers (e.g., Amazon Redshift, DynamoDB, Amazon EMR) whereas insights need to be derived by not just developers but also non-technical business users. Big data challenges. Enter Amazon QuickSight.

Cloud 133

Cloud Big Data AWS Analytics 133