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Like any other, Data engineering is one of the popular rough and tough career paths in the technology department. Organisations strive to collect insights into large databases and statistics, requiring a person with data science tools and analytics expertise.
So those who are looking to shape a bright future and career in data engineering, this guide is for you. Read ahead to understand the concept of data engineering, its potential roles and the required skills to become one.
For those looking for what exactly a data engineer means? A data engineer is a skilled individual who is accountable for planning, designing, developing and managing all things data according to the organization’s requirements. They work to process a smooth flow of data whenever required to make it understandable and accessible to the needed ones.
For a fact, they are known as the building blocks of any organization, as they are responsible for extracting reliable data, converting it into a useful resource and keeping it safe in the systems.
Data is the core priority of the company, and data engineers play a critically important role in managing the data cycle in any sector of business.
Information is the primary source for any type of industry. However, the process of extracting it and making it accessible can seem to be a tedious task. The data engineers arrive as a saviour. Holding prior experience in managing data pipeline development, they are responsible for collecting, creating and quoting valuable insights in a readable form to ensure a smooth workflow.
Manipulating the raw and unstructured data is not everyone’s cup of tea. That is why the company relies on data engineers to manage their all data-related work. To ease down the process, data engineers use ETL (Extract, Transform, load) to structure the clean and formatted data, making it available for further analysis.
Where data is known to be a significant asset of any company, keeping it safe from losing it to any vulnerabilities includes the job role of a data engineer. They ensure the databases are stored in the right manner and can be accessed easily whenever required.
Data security and compliance with GDPR are essential to maintain the overall reputation of your company or brand. To protect the company’s sensitive and confidential information, data engineers implement robust strategies and techniques.
The role of data engineers requires hardcore technical skills and knowledge. So those who are planning to pursue education in the same should buckle up and focus on the learning process. For those looking for preparation material, Databricks-Certified-Data-Engineer-Associate Exam Question and Answers can be the best choice.
To pursue a bright future and career as a data engineer, a set of skills and knowledge is crucial to withstand the job role. Foundations in computer science or tech departments can add brownie points in further learning processes.
Furthermore, check out the process to reach your final destination.
Research for the courses and Databricks certification exam in your geographical location. Plan to relocate if you find a promising opportunity. Start with pursuing a bachelor’s degree and further with the required certified courses as it builds a strong background in basic programming and database system management.
To start with the learning process, acquiring the basic data-savvy skills can help you understand the technicalities and complexity of this field. Proficiency in coding languages like Python, Java, SQL and more is the prime requirement of this niche. Familiarize yourself with the cloud platforms, frameworks, technical tools and more.
After getting completed with the degree, move on to establish a practical experience to face the realm of this field. Seek internships or projects as a trainee and work under experts to enhance your practical knowledge. Moreover, exposure to a working environment will help you to build a potential reputation and contacts.
A portfolio speaks on your expertise on behalf of you. The very first step to take before planning to search for a job is to build a robust portfolio that leaves a compelling impression on the hiring recruiters. Add your personal information, and along with that add the details of the projects you worked on and the achievements. Mention your soft skills to make it more authentic.
To inaugurate your career as a data engineer, start applying for entry-level positions to gain more required experience and expertise. During your first-ever job, polish your skills, undergo new challenges, explore different fields and niches. The day you will be equipped with the required knowledge and skills, you are all set to start your bright professional life.
So whether you are a student, a beginner, or a trainee, the journey of becoming a data engineer involves a continuous learning process.
Adhering to the challenges coming your way is also crucial, along with the data engineer benefits to not regret your decision in the future.
| PROS | CONS |
| ✔️ Increased demand across every industry. | ❌ Work pressure and deadlines. |
| ✔️ High-tech salary and additional perks. | ❌ Continuous learning is necessary. |
| ✔️ Flexible working shifts. | |
| ✔️ Contribution to the future of technology. | |
| ✔️ Department with high job opportunities. |
Despite a few cons, data engineering has proven to be a demanding career in today’s advanced world.
Before entering the career, take into account all the learning processes, time, costs, practical experience, day-to-day job responsibilities and more to prepare yourself to enter the exciting path of your life.
As technology is undergoing innovations regularly, the demand and value of data engineers will increase in the coming decade.
Ans: Completion of a bachelor’s degree that takes up to 3 years is necessary to get an entry-level position in data engineering. Moreover, some jobs also require extra advanced certification.
Ans: A background in computers and IT department is suitable for this field. However, by learning programming and acquiring the required skills, a non-technical person can also excel in this field.
Ans: Python, SQL, and Java are the primary coding languages to succeed in the role of data engineering.
