Roadmap to becoming a data engineer

Data engineers are professionals who build systems responsible for collecting, managing and transforming data into formats that could be used by data scientists. Becoming a data engineer is a lucrative career choice for many students with a background in computer science. However, entry into this field is relatively difficult. Hence you need to stick to a strategy and roadmap in order to learn the skills needed for getting a job as a data engineer. So here we have made a roadmap showing the skills you need to master for becoming a highly-paid data engineer:

1. SQL

SQL is the programming language that data scientists use to analyze and manipulate data.  If you want to become a data engineer, you need to know how to write SQL queries yourself.SQL is widely used in many companies, even if they don’t offer it as a separate tool. It’s used at companies like Amazon, Google and Facebook, as well as many other companies around the world.SQL is the language that drives data science in the cloud. It’s a programming language used to query and manipulate data, which is what makes it so important for data engineers.

SQL allows you to create and manage databases on a server, which means you can store your data in one place and access it from any device. You can also use SQL to perform complex calculations like joining multiple tables or aggregating information from multiple rows of data into one result set. Hence, SQL programming is not only a part of SQL developer roles and responsibilities. It is also equally important for a data scientist and data engineer. 

2. Amazon Web Services (AWS)

Amazon Web Services (AWS) is one of the most popular cloud computing platforms in the world, with hundreds of thousands of customers around the globe using its products every day. AWS offers several services designed specifically for data scientists including Amazon Redshift, Amazon Athena and Amazon EMR that make it easy for them to analyze massive amounts of structured or unstructured information stored. The biggest proof of its usability is that Amazon Web Services (AWS) is one of the largest cloud computing platforms in the world, with over 100,000 active customers and over 12 million developers using its services every month!

3. Hadoop

Hadoop is a software framework that makes it easier for programmers to store and analyze large amounts of data across multiple machines in a cluster environment. This has become a popular choice for storing data in recent years because it allows for much faster access times as compared with other options such as MongoDB or Cassandra. Hadoop is the best open-source software framework for handling big data on clusters of commodity hardware. It can be used for batch processing or stream processing — that is, performing computations on streams of data as they arrive rather than storing them in files or databases first.

4. Kafka

Kafka is a distributed streaming platform that allows applications to read and write data to different nodes. It’s a pub-sub messaging system that can be used to create real-time applications, including IoT, in-memory databases, and mobile apps. It’s a publish-subscribe model, where producers send messages to multiple consumers in order to get them out of their Kafka cluster. The message may be any form of structured or unstructured data, including real-time events or financial market information. This is the best distributed messaging system designed to provide high throughput and low latency for real-time data processing. Use Kafka to process billions of events per second with near-linear scaling.

5. Python

Python is another programming language that you will need if you want to become a data engineer. It’s easy to learn and has a great community of developers who help each other out with code issues and questions. Python also makes it easier for you to integrate different technologies from different vendors. Python is a popular programming language that’s used in data science and data engineering fields. Python is also used by many companies for machine learning projects, which makes it an excellent tool for data engineers working with large amounts of structured and unstructured data. If you want to become a data engineer you would need a deep knowledge of Python. Hence you should spend time studying Data Structures And Algorithms In Python and also work on some python related projects.