Big data has benefitted many individuals to get high-salary careers. Big data professionals have a huge market demand in the current market.
Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn.
What is data engineering?
Data engineering is the process of developing and building systems for collecting, storing, and analyzing data. It is a vast field with several applications in various industries. Firms have collected huge amounts of data, and they require data infrastructure and personnel to sort and analyze the information.
This resulted in the demand for big data engineers who work to design systems, which collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. The main objective is to make data accessible so that the firms can take help of it for evaluating and optimizing their business overall performance.
In this article, let’s talk about the crucial aspects that an individual needs for a career in data engineering.
Earn an undergraduate degree
The most important aspect to start your career in the field of data engineering is to have a bachelor’s degree, as the job demands a good knowledge of various basic concepts. One can do a degree in any of the following:
- Computer Science
- Software Engineering
- Information Technology
Have a good sense of programming
The field of data engineering requires good coding skills. A data engineer must have a programming background. They must have a keen interest in data as well as finding patterns in data. One can enhance their knowledge of the programming languages by doing a big data certification. The important programming languages one must have knowledge of are as follows:
Learn latest technologies
The individuals must have a good knowledge of the latest technologies that are essential to perform the day-to-day tasks. Following are the important tools that the data engineers use:
- Apache Hadoop
- Apache Spark
- Apache Hive
- Apache Beam
- Apache Cassandra
- Apache Oozie
- Apache NiFi
- Apache Flink
- Apache HBase
- Apache Impala
- Apache Kafka
- Apache Crunch
- Apache Apex
- Apache Storm
One can also start with the three giants in the market: Google Cloud Platform (GCP), Microsoft Azure, and Amazon Web Services (AWS). Learning these latest technologies will help an individual to offer the best inputs, which can be used for developing scalable data pipelines.
Develop communication skills
It is very important to develop one’s communication skills to be part of this growing field. A good big data engineer should have the following qualities:
- Communication skills: This job role demands interacting with people like stakeholders to know their demands before development.
· Ability to design: In their job role a data engineer creates simple creative designs where the architecture is not overly done.
- Detail-oriented: Data quality plays a key role in developing data pipelines. The quality and integrity of the data in the pipeline will determine the quality of the rest of the task.
Get professional certifications
There are several industry-recognized data engineer certifications that an individual can do to enhance their skills before starting their career in this field. Certification offers excellent knowledge and guidance by giving exposure to real-time projects.
Gain entry-level job experience
One of the best aspects to get entry into the field of data engineering is, getting an entry-level job. There are many firms especially start-ups who are offering positions for qualified graduates. Once you gain good experience, try solving problems by choosing public data sets and develop a system.
If an individual wants to start their career in the field of data engineering, they must enhance their skillset and do a certification program that offers better knowledge. It is highly recommended to stay updated with the latest technologies.