Remove Coding Remove Database-centric Remove Software Engineering
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The Rise of the Data Engineer

Maxime Beauchemin

Like data scientists, data engineers write code. Unlike data scientists — and inspired by our more mature parent, software engineering  — data engineers build tools, infrastructure, frameworks, and services. It’s also fairly common for engineers to develop and manage their own job orchestrator/scheduler.

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How To Become a Project Manager From Software Engineer?

Knowledge Hut

Picture yourself as a software engineer leading a team to launch new products and services for different clients. Software engineering is all about crafting lines of code to offer innovative solutions for enhanced business growth. What Does a Software Engineer Do?

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How to manage and schedule dbt

Christophe Blefari

But this article is not about the pricing which can be very subjective depending on the context—what is 1200$ for dev tooling when you pay them more than $150k per year, yes it's US-centric but relevant. If we do a parallel with software development, this is your codebase. Data engineering or analytics team?

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Every Company is Becoming a Software Company

Confluent

Of course, this is not to imply that companies will become only software (there are still plenty of people in even the most software-centric companies), just that the full scope of the business is captured in an integrated software defined process. These applications are all what software engineers call “CRUD” apps.

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Data News — Week 23.14

Christophe Blefari

I still firmly believe that this is not the role of a data engineer. A data engineer should still be a software engineer working with data, empowering others with tooling and apps. Data modeling should not be a required data engineer skill. Enters the analytics engineer. I hope he will fill the gaps.

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Data News — Week 13.14

Christophe Blefari

I still firmly believe that this is not the role of a data engineer. A data engineer should still be a software engineer working with data, empowering others with tooling and apps. Data modeling should not be a required data engineer skill. Enters the analytics engineer. I hope he will fill the gaps.

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Building a maintainable and modular LLM application stack with Hamilton

Towards Data Science

In this post, we’re going to share how Hamilton , an open source framework, can help you write modular and maintainable code for your large language model (LLM) application stack. The example we’ll walk you through will mirror a typical LLM application workflow you’d run to populate a vector database with some text knowledge.