The Agile Manager

JULY 31, 2022

There are shadow IT teams of developers or data engineers that spring up in areas like operations or marketing because the captive IT function is slow, if not outright incapable, of responding to internal customer demand. IT shadows appear in a lot of different forms. The scope taken out of the 1.0

Programming 59

Programming Engineering Data Engineering Innovation 59

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. SUS312 How innovators are driving more sustainable manufacturing  — Marcus Ulmefors Northvolt Director Data and ML Platforms and Muhammad Sajid AWS SA.

AWS 64

AWS Energy Architecture Programming 64

O'Reilly

FEBRUARY 18, 2020

The results for data-related topics are both predictable and—there’s no other way to put it—confusing. Starting with data engineering, the backbone of all data work (the category includes titles covering data management, i.e., relational databases, Spark, Hadoop, SQL, NoSQL, etc.). This follows a 3% drop in 2018.

Software Architecture 134

Software Architecture DevOps Data Engineering Architecture 134

O'Reilly

FEBRUARY 2, 2020

Collaboration between AI developers and operations teams will lead to growing pains on both sides, especially since many data scientists and AI researchers have had limited exposure to, or knowledge of, software engineering. It’s going to be an interesting few years as operations assimilates AI.

Software Architecture 68

Software Architecture Monitoring Software Engineering Architecture 68

All Things Distributed

OCTOBER 7, 2015

However, the data infrastructure to collect, store and process data is geared toward developers (e.g., In AWS’ quest to enable the best data storage options for engineers, we have built several innovative database solutions like Amazon RDS, Amazon RDS for Aurora, Amazon DynamoDB, and Amazon Redshift.

Cloud 138

Cloud Big Data AWS Analytics 138

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.” Please share your experience by adding your comments below and stay tuned for more on data lineage at Netflix in the follow up blog posts. .

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

The Netflix TechBlog

OCTOBER 30, 2020

I’m a Senior Analytics Engineer on the Content and Marketing Analytics Research team. My team focuses on innovating and maintaining the metrics Netflix uses to understand performance of our shows and films on the service. But what do I actually do? Besides eating breakfast) What do I do at Netflix?

Analytics 136

Analytics Engineering Innovation Metrics 136

Abhishek Tiwari

FEBRUARY 26, 2020

Skills++: Induct specialised Frontend, Backend & QA engineers, Technical Leadership 21-30 Engineers Focus: Building quality in products and continue to innovate while proactively planning team structure, incentives, and culture. Introduce site-reliability engineering best-practices (SLI/SLOs).

Technology 81

Technology Technology Architecture Engineering 81

Abhishek Tiwari

JULY 20, 2019

I also have a strong feeling that long-lived teams are not good for innovation and disruption. Contrarian view What I am proposing here is some key principals to change how you deploy your engineers to do their best work in a fast-paced environment. Teach your engineers how to do teaming, reteaming, and onboard new team members.

Engineering 61

Engineering Retail Airlines Healthcare 61

The Netflix TechBlog

SEPTEMBER 10, 2019

Our data scientists faced numerous challenges in our previous infrastructure. Complex business logic was embedded directly into the ETL pipelines by data engineers. In order to replicate results, scientists had to delve deep into the data, code, and documentation. This is an ongoing journey.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

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. Let’s walk through some of the core experiences of QuickSight that make it so easy to set up, connect to your data sources, and build visualizations in minutes.

Analytics 152

Analytics Availability Media Social Media 152

The Netflix TechBlog

JANUARY 11, 2022

Here we describe the role of Experimentation and A/B testing within the larger Data Science and Engineering organization at Netflix, including how our platform investments support running tests at scale while enabling innovation. Curious to learn about what it’s like to be a Data Engineer at Netflix?

Innovation 243

Innovation Metrics Engineering Testing 243