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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

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.

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Spice up your Analytics: Amazon QuickSight Now Generally Available in N. Virginia, Oregon, and Ireland.

All Things Distributed

They require companies to provision and maintain complex hardware infrastructure and invest in expensive software licenses, maintenance fees, and support fees that cost upwards of thousands of dollars per user per year. Data is automatically replicated across multiple Availability Zones for redundancy and also backed up to S3 for durability.

Analytics 152
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A Day in the Life of an Experimentation and Causal Inference Scientist @ Netflix

The Netflix TechBlog

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.

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

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?

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What is IT automation?

Dynatrace

This requires significant data engineering efforts, as well as work to build machine-learning models. Big data automation tools. These tools provide the means to collect, transfer, and process large volumes of data that are increasingly common in analytics applications. Creating a sound IT automation strategy.

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Experimentation is a major focus of Data Science across Netflix

The Netflix TechBlog

Curious to learn more about other Data Science and Engineering functions at Netflix? To learn about Analytics and Viz Engineering, have a look at Analytics at Netflix: Who We Are and What We Do by Molly Jackman & Meghana Reddy and How Our Paths Brought Us to Data and Netflix by Julie Beckley & Chris Pham.

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

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.