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Sustainability: Thoughts from a software engineer

Dynatrace

Until recently, improvements in data center power efficiency compensated almost entirely for the increasing demand for computing resources. The rise of big data, cryptocurrencies, and AI means the IT sector contributes significantly to global greenhouse gas emissions. However, this trend is now reversing.

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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

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. What is your favorite project?

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Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

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A Recap of the Data Engineering Open Forum at Netflix

The Netflix TechBlog

Creating new development environments is cumbersome: Populating them with data is compute-intensive, and the deployment process is error-prone, leading to higher costs, slower iteration, and unreliable data. To handle errors efficiently, Netflix developed a rule-based classifier for error classification called “Pensive.”

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Data Engineers of Netflix?—?Interview with Dhevi Rajendran

The Netflix TechBlog

Dhevi joined Netflix in July 2020 and is one of many Data Engineers who have onboarded remotely during the pandemic. In this post, Dhevi talks about her passion for data engineering and taking on a new role during the pandemic. One great thing about working with data is the impact you can create as an engineer.

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing.

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Data Engineers of Netflix?—?Interview with Samuel Setegne

The Netflix TechBlog

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. Samuel Setegne is a Senior Software Engineer on the Core Data Science and Engineering team.