Top 10 Resources for Data Engineers
In the ever-evolving landscape of data engineering, staying up-to-date with industry trends, the latest tools, and best practices is paramount. Your responsibilities likely span from the design and construction of large-scale data processing systems to the transformation of raw data into useful, analytical gold.
To support you in your mission, we've compiled a list of the top ten resources that we believe every data engineer should be familiar with.
Whether you're just starting on your data engineering journey or you're a seasoned professional looking for some fresh insights, these resources are sure to provide a wealth of knowledge and practical skills to help propel your career forward.
A weekly podcast that covers a wide range of topics relevant to data engineering. It features discussions on data architecture, technical challenges, and deep dives into both open-source and paid offerings. This is a great way to stay current with the latest trends and discussions in the field. (Check out the episode with our CEO!)
This GitHub repository contains a curated list of resources specific to data engineers, including subsections for databases, ingestion, workflows, and datasets. It provides a vast array of resources that can be very useful to data engineers.
This is an extensive platform with resources in multiple formats including podcasts, articles, presentations, and more. It's an editorial community with engineers and practitioners rather than journalists, covering a wide range of topics including AI, machine learning, and data engineering.
A fantastic book that covers planning, designing, and structuring modern databases, which is a fundamental skill for data engineers.
This book is a comprehensive resource for learning data modeling. It covers the most up-to-date data modeling techniques, including enhanced star schema dimensional modeling and more.
A free resource highly recommended for understanding how to manage sensitive data and establish compliance with regulations like GDPR and CCPA. This is increasingly important in modern data engineering practices. (Polytomic is a GDPR-compliant ETL tool.)
This site is a leading resource on AI, analytics, big data, data mining, data science, and machine learning. It provides news, tutorials, courses, datasets, webinars, and more that can be helpful for data engineers.
DB-Engines is a website that ranks database management systems. It's a great resource for data engineers to stay updated about popular databases, their comparisons, and trends in the industry.
This Reddit community is dedicated to the field of data engineering. It's a great place to network, learn, share resources, ask questions, and discuss issues related to data engineering.
This is a seminal book that provides comprehensive knowledge about the different systems that data engineers frequently work with, including databases, search indexes, and more. It helps in understanding how data flows through these systems, which is crucial for data engineers.
11. Polytomic [bonus resource]
We would be remiss not to mention our product as a resource for data engineers. Data engineers use Polytomic to sync any data anywhere. ETL, Reverse ETL, CDC, iPaaS, and APIs all in one easy-to-use platform. No more manual data pipeline maintenance. Check out the rest of our website!
The resources we've curated for you - from influential books and informative podcasts to invaluable online courses, software tools, and thriving online communities - are designed to offer a balanced mix of theoretical knowledge and hands-on skills.
Whether you're navigating the complexities of a new tool, seeking to connect with fellow data engineering professionals, or simply keeping abreast of the latest industry trends and news, there's a resource in this list that's ready to meet your needs.
Remember, your journey as a data engineer is one of constant exploration, learning, and adaptation. Make the most of these resources to continue growing, enhancing your skills, and staying at the forefront of your field.