Show HN: 20 years of data engineering experience compiled into a toolkit

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To thrive as a data engineer, you need various skills—from fundamental (Linux commands, containerization, programming languages) to Kubernetes orchestration. The data engineering toolkit provides the building blocks of data engineering work in 2025.

Multiple

Programming Languages

Essential operating system knowledge and command-line skills for every data engineer

💻

Development Environment & IDE

Modern development environments, editors, and cloud-based coding platforms

SQL

Data & SQL Fundamentals

The core data technologies that every data engineer must master

The language of data engineers with extensive library ecosystem

📊

Data Skills & Architecture

Understanding data flows, modeling, and business requirements

📈

Analytics, BI & Orchestration

Tools for data transformation, orchestration, and business intelligence

⚙️

DevOps & Infrastructure

Modern deployment, orchestration, and infrastructure management

🛠️

Advanced Tools & Storage

Specialized tools for enhanced productivity and modern data infrastructure

🤖

AI Workflows & Integration

Emerging AI integration and workflow automation capabilities for modern data engineering

🔍

Data Quality & Observability

Essential tools for monitoring, validating, and ensuring data reliability and governance

# Explore Further

This toolkit represents the essential technologies that not every data engineer must know from the beginning, but might over time. For deeper exploration of concepts, methodologies, and the evolving landscape of data engineering, dive into the Data Engineering Vault—a comprehensive knowledge network with 1000+ interconnected terms and concepts.

Blogs: If you prefer an article, here they are:

The Data Engineering Toolkit: Essential Tools for Your Machine (Part I)
The Data Engineering Toolkit: Part II (coming soon)

# A Brief Evolution of Data Engineering

Data engineering has evolved from traditional ETL and database administration to a comprehensive discipline requiring system administration skills and advanced cloud-native expertise. Modern data engineers must get more comfortable with everything from Linux command-line operations and setups like Kubernetes orchestration, making it one of the most technically diverse roles.

Even more so, DevOps is the new data engineering I’d say. Most of a data engineer’s work today involves setting up tools with a code-first approach, emphasizing automation, reproducibility, and infrastructure as code, especially if you work with open-source DE. Read more on Data Engineering Vault about Evolution.

Origin: Essential Data Engineering Toolkit
References: The Datawarehouse Toolkit - Ralph Kimball
Created 2025-06-19

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