Ever wondered how companies use the data they collect? And how it matters? How do they convert data into crucial information? And how are solutions developed for using this data? If these questions intrigue your curiosity, you may want to look into becoming a big data engineer. What is a big data engineer, you ask? Let us introduce you to the bright field of big data engineering. Big data engineering is a vast field that has a bright future and scope in the world’s new technological era.
This field covers data collection, data processing, and many related areas. MNC’s and other private companies hire big data engineers to make use of the data they have gathered through research findings. Big data engineers are responsible for building data reservoirs and managing those complicated reservoirs. They have to develop and ensure the functionality of data-storing infrastructures, such as databases and large-scale storage processing units. Here’s everything you need to know about the in the making field of big data engineering.
“What is a big data engineer?” is a common question encountered concerning this field. As we said, data engineering is the branch of data science that primarily focuses on the practical application of data analysis, processing, and collection. Like most branches of engineering, data engineering, too, deals with applying the gathered data science in practical applications of the real world.
Therefore, in simple and non-professional terms, data engineering is focused on developing smooth-functioning systems for better flow and access to the company’s information. Similarly, a big data engineer is a person who is responsible for creating and managing a company’s Big Data tools and equipment. A big data engineer has to scan through the vast databases of information to find quick solutions as per the company or client’s requirements.
The walls of Big Data engineering has expanded significantly during the last two decades. That makes big data engineering one of the highest paying and the most prosperous profession one can have in 2022. However, the actual definition of this role may vary from company to company and according to their requirements. Most people confuse a big data engineer with a data scientist. It is a common mistake.
As we said, confusing a big data engineer with a data scientist is a common and unintentional mistake. However, if you want to clear your doubts, here is the difference between a big data engineer and a data scientist. The most significant point of difference between a big data engineer and a data scientist is that data scientists work to develop solutions whereas big data engineers create systems that help to implement them. That means, data scientist work on the abstract, and big data engineers work on practical projects. Both of them are equally important as a world without data scientists would have no use for big data engineers. Similarly, without a big data engineer, the work of a data scientist wouldn’t have any value.
The big data engineer job description involves mainly to develop and maintain architectures like databases. They supervise the process of collection of data and the conversion of the raw data into usable information.
Therefore, without a big data engineer, you can’t collect data. For that, companies require their data engineers to be familiar with Java, AWS, Scala, and SQL along with similar programming languages. A big data engineer job description also requires a strong background in backend development along with programming. If you are a big data engineer, you will have to manage the process of collection of data, handling its storage, and processing it for further use.
A big data engineer job description requires many skills. Some of the common skills include data structuring, knowledge of Java, and Big Data, that is, Hadoop and Kafka. Even though the professional requirements for each big data engineer can vary from employer to employer and their client requirements, there is a common set of skills that every big data engineer has to be adept in. On that note, let’s explore how to be a big data engineer and the educational and professional qualifications required for being one.
Big data engineers typically need an undergraduate degree in math, science, or a business-related field. The expertise gained from the 4 years of this degree allows them to use programming languages to mine and query data. In some cases, knowledge of SQL programming languages is also needed.
Now, depending on the particular big data engineer job description and industry, most big data engineers get an entry-level type job with their bachelor’s degrees. However, some companies may demand advanced degrees in STEM fields and professional engineering or big data certifications. To sum up, here is what you need to do to be a big data engineer:
Given the importance of data engineering and STEM fields, individuals with computer and information technology skills are in high demand. Lastly, to be a big data engineer and to be successful in your career, you will have to be familiar with the following concepts and programming languages:
Big data engineering is one of the highest-paying professions in the global market. Big data engineers take an average of $116, 591 per year. And, if you are a senior big data engineer, your average salary will be around $148, 216 gross per year. In conclusion, the field of big data engineering is big. And, there is a huge demand for people with the appropriate skills and certifications. Thus, if you are interested, you should definitely look into this.