Introduction

This has been inspired by the Full Stack Developer's Roadmap post written by @ender_minyard

With the ever growing data volumes and demands, the data engineering career has been one of the fastest growing jobs for the past few years.

According to the 2021 Stack Overflow survey, data engineers are one of the top 5 highest paid professionals right after SREs and DevOps engineers:

If you are looking to become a data engineer, here are some resources for data engineering that you can save for later.

Table Of Contents

• Fundamentals
• Programming basics
• Testing
• Database Fundamentals
• Data warehouses
• Object storage
• Data processing
• Messaging
• Cluster computing
• Workflow Scheduling
• Monitoring data pipelines
• Infrastructure as Code
• CI/CD

Fundamentals

Having a solid understanding of the Linux operating system could be a must in many IT related roles. You are going to benefit a lot if you know the basics of the following:

• Basic Terminal Usagehttps://devdojo.com/course/linux-command-line-basics
• Shell Scripting
• Git and GitHub
• Networking

Programming basics

As with any IT related role it is essential to have fundamental knowledge of programming in general. The programming language itself does not matter that much, but you need to have good understanding of programming paradigms and best practices.

• Python
• Java
• Go
• PHP

Testing

• Unit Testing
• Functional testing

Database Fundamentals

Having a solid understanding of SQL, data normalization and ACID transactions is a must for all data engineers.

• SQL basics
• OLTP vs OLAP
• Horizontal vs vertical scaling

Relational Databases

• MySQL / MariaDB
• PostgreSQL

Non-relational databases

• Document: MongoDB, Elasticsearch
• Wide column: Apache Cassandra, Apache HBase
• Graph: Neo4j
• Key-value: Redis, Memcached

Data warehouses

• Snowflake
• Presto
• Apache Hive

Object storage

• AWS S3
• DigitalOcean Spaces
• Google Cloud Storage

Data processing

Batch

• Apache pig
• Apache Arrow

Hybrid

• Apache Spark
• Apache Beam

Streaming

• Materialize - The Streaming Database for Real-time Analytics
• Apache Kafka
• Apache Storm

Messaging

• RabbitMQ
• Apache ActiveMQ

Cluster computing

• Apache Hadoop and HDFS
• MapReduce

Workflow Scheduling

• Apache Airflow
• Apache Oozie

Monitoring data pipelines

• Prometheus
• Datadog

Infrastructure as Code

• Containers: Docker
• Orchestration: Kubernetes, Docker Swarm
• Provisioning: Terraform
• Automation: Ansible

CI/CD

• GitHub Actions
• Jenkins

Conclusion

This was inspired by the Data Engineer Roadmap open source repository here:

https://github.com/datastacktv/data-engineer-roadmap

I wanted to build upon the roadmap and provide a list of resources for each topic.

Let me know if I've missed anything! Hope you find this useful and make sure to keep learning

You can follow me on Twitter at: @bobbyiliev_