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The Data Engineering Toolkit
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.
Essential operating system knowledge and command-line skills for every data engineer
Modern development environments, editors, and cloud-based coding platforms
The core data technologies that every data engineer must master
The language of data engineers with extensive library ecosystem
Understanding data flows, modeling, and business requirements
Tools for data transformation, orchestration, and business intelligence
Modern deployment, orchestration, and infrastructure management
Specialized tools for enhanced productivity and modern data infrastructure
Emerging AI integration and workflow automation capabilities for modern data engineering
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