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How to Become A Remote Data Engineer

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How to Become A Remote Data Engineer

Data engineers are experts that help collect, organize, and store data for analytical or operational uses. They manage existing data architecture and think of ways to make them better. They also ensure that the data collection and storage processes meet the industry standard. In addition, they create custom software for merging and analyzing data.

Data engineering is a lucrative and highly demanded job; an average data engineer earns over $110,000 per annum. High-ranking data engineers earn almost $200,000. Another advantage of data engineering is that you don’t have to do it on-site. Instead, you can find the job of a remote data engineer right from the comfort of your home.

However, getting a data engineering job can be challenging. You need a great deal of education and skills to break into this data world. To make life easier, we have collaborated with professionals from job aggregator Jooble to enlighten you on the requirements needed to explore this profession and how to go about it.

Steps Towards Becoming A Data Engineer

Being a data engineer is a technical and demanding job. It requires a lot of processes and training to get into it fully. It also requires patience and tenacity to become one, but the pay is worth it.

Below are the processes for becoming a data engineer:

1. Get A Degree

You must have a university degree to be employed as a data engineer. A degree in mathematics, physics, computer science, statistics, or engineering is usually considered. It takes about four to five years to get a degree.

2. Hone the Necessary Skills

While getting your degree, start honing the necessary skills needed to become a data engineer. Start by learning and perfecting SQL.

Then, as you gain the skills, make sure to put them to use, as this is how you can get better at what you do. A more comprehensive explanation of the skills required of a data engineer will be done further in this article.

3. Gain Some Experience

It is no news that it can be challenging to get a job without some real-life experience. So start gaining experience to build your portfolio as early as possible. You can begin by doing internships and volunteer jobs while at the university.

4. Get Entry-Level Job

Data engineering has some processes, and starting from the top is impossible. Instead, start your data engineering career by applying for apprenticeships or entry-level jobs.

5. Get Advanced Certifications

It is advisable to keep up with the job market demand to advance as a data engineer. In addition, you should get advanced certifications to improve your chances of employment. Further certifications can also help you negotiate better pay.

Some of the certifications to consider are:

  • Google Certified Data Engineer Certification;
  • Google Professional Data Engineer;
  • Data Council of America (DASCA) Associate Big Data Engineer.

6. Consider A Higher Degree

While a bachelor’s degree is the recommendation for getting a data engineering job, earning a master’s degree or a Ph.D. will put you on higher ground. Also, a higher degree is crucial if you are considering applying for a top data engineering position in the future.

7. Apply For Remote Data Engineering Jobs

After dotting your ‘Is’ and crossing your ‘Ts,’ it is not time to relax but to start looking for a job. First, prepare your CV and search online sites for data engineering jobs. Also, you can update your LinkedIn account to find openings quickly.

Also read: How To Protect Your Devices From Malware: 2022 Tips

Important Skills For A Data Engineer

Apart from the steps taken, some skills are necessary for data engineers. Most of these skills are related to computers and IT. Therefore, you must have solid computer knowledge before starting.

Below are the crucial skills you must possess to thrive as a data engineer.

Coding

Coding is one of the primary skills of a data engineer. This knowledge is necessary as the job requires that you create a great data pipeline for data transmission, storage, and analysis. Therefore, it is essential for anyone interested in data engineering to learn to code. Programming languages that you can learn include Java, Python, NoSQL, Kala, R, etc.

Data Warehousing

The major duty of a data engineer is to store data and make it accessible when necessary. Data warehousing, as the name suggests, involves storing data. It consists in capturing datasets from different places and putting them into the form of a database.

Data warehousing makes it more straightforward to assess datasets. It also makes it easier for corporate directors and organizations to arrange their data and have an insight into the situation of their company.

Knowledge of The Operating System

The operating system is the brain of the computer as it helps manage the computer’s processes and memory. Meanwhile, data engineers store their data on computers, and all their work is done on the computer, and they interact with the computer to build databases. They need to have great knowledge of the OS as it helps them interact with the computer better.

SQL

Structured Query Language (SQL) is the most important programming language used by data engineers. It is used to design and create databases. It can also be used to make queries to a database or draw insights from it.

Although it might take a lot of time to master it, proficiency in it is vital if you want to become a data engineer.

Data Architecture

Data engineering involves building databases to structure, organize, and store datasets. This building process can be likened to building a house. It is essential to have a good plan and a clear foresight to do that successfully. Data architecture is creating a blueprint for successfully doing the job of data engineering.

Conclusion

No doubt, data engineering is a complex job. It requires a good educational background, some experience, and skills. It is also worth noting that being a data engineer is not a day’s job, and the process can be challenging. However, following the directions above will kick-start your breakthrough in the data engineering career.

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