Over the years, Big data has emerged as one of the prominent technologies across all excellently performing industries. All major enterprises make decisions that are guided by the insights driven from the analysis of big data. Big data holds a huge potential for those who like playing with numbers. And to become a big data engineer, all you need to do is to enroll in a big data engineering course and acquire relevant skills. Through this article, you’ll learn about the major skills that all big data engineers need to gain for having a rewarding career ahead. So let’s ot waste time and get started.
Top Skills for Becoming a Big Data Engineer
The top skills that big data engineers need to acquire include:
1. Machine Learning
Machine learning is considered one of the most important tools for big data engineers as it enables them to refine and process enormous volumes of data in a very short span of time. Big data forms the major part of machine learning algorithms as the machines learn by processing data sets. Therefore big data engineers need to be aware of the machine learning algorithm building process and know how to use them in the data ingestion process.
2. Database Tools and Skills
Databases form the core of data storage, searching and organizing. Because of this, it’s highly essential to be familiar with their structure and language. There are majorly two types of databases SQL based and NoSQL based. Over the years, NoSQL has gained more popularity and therefore one must know about different types of NoSQL.
3. Hadoop
Hadoop is primarily a series of open-source libraries that processes large datasets on huge numbers of servers and devices altogether. It has various types of scales as per the data and mode it runs in. Big data engineers need to be aware of the modes and the purpose they are used for.
4. Java
Java is the most frequently used coding language because of its simplicity, efficiency and object-oriented quality. Also, it’s one of the most popular languages for building data sorting algorithms and machine learning sequences. Because of this, it’s one of the major skills for big data engineers and they must be proficient in it. Engineers must know how to write automated scripts and be aware of machine learning libraries such as Java ML.
5. Python
Python is another highly popular programming language because of its versatility. It has a huge community and a wide number of libraries. Due to this, big data engineers must ensure that they are proficient in Python and ensure that they are involved in contributing to Python libraries and also drawing from them.
6. Apache Kafka
It’s an open-source software processing platform based on Scala and Java. It’s capable of handling real-time data and can easily connect to outside processing libraries. Big data engineers need to be well versed with Kafka’s architecture, its usage and the methods to integrate with different libraries.
7. Scala
Scala is primarily a general-purpose coding language commonly used in data processing libraries such as Kafka and therefore it’s important for data engineers to have knowledge of Kafka.
8. Apache Spark
It’s one of the most important tools for data engineers. It’s an open-source, distributed cluster computing unified analytics engine that is used for large data sets and offers an interface for programming clusters. It’s essential for big data engineers to know how to operate both frontend and backend and also on Spark libraries and the Spark cluster.