The job of a Big Data Engineer is highly strategic. You will be entrusted with several responsibilities including developing high-performance algorithms, proof of concepts, predictive models, and data set processes used for data mining and modeling. With big data skills, you will be able to find employment in major tech companies as well as small startups. But, before you enter the world of Big Data Engineering, you should know exactly what it is and what it takes to become one and stay relevant.
Big Data Engineers have to build massive data reservoirs and manage them along with the data created by digital activities. They create, test as well as maintain architectures like data processing systems and databases. As a big data engineer, you will be installing continuous pipelines running to and from pools of filtered information. This information is then used by data scientists for pulling relevant datasets that they can use for their analysis. Here are a few of the responsibilities you will have as a Big Data Engineer:
- Ensure that the data collection and storage system is meeting the requirements of the business and has acceptable industry standards.
- Integrate new software for data management into the existing structures of the company and look for new opportunities for data acquisition. This involves finding efficient ways of bringing in data from a new client.
- Create custom components of the software using different tools and languages for merging different systems together. This also involves developing a strong analytics infrastructure to measure the data stored by the business.
- Store and process data securely. As a Big Data Engineer, you will be on the frontlines of your organization’s cyber defenses. You will be responsible for installing and updating protocols for disaster recovery and recommending ways for improving data quality and reliability.
How to become a Big Data Engineer?
Usually, Big Data Engineers have a Bachelor’s degree in computer science, math, or a business field. During the degree program, they gain expertise in using programming languages for mining and querying data and even use big data SQL engines. Once you have completed your undergraduate program, you will be able to get an entry-level job.
If you plan to become a Big Data Engineer, here are a few steps that you should follow:
1. Get a Bachelor’s degree and start working on projects
If you want to enter the field of Big Data, you must get a bachelor’s degree in software or computer engineering, computer science, physics, statistics, applied math, or any related field. Another important thing that you must have to become qualified for an entry-level position is real-world experience. You can get this through internships. If your undergraduate program is from outside of these fields, you can take up a course on Big Data, Data Structures, Database Management, Algorithms, or Coding. You have to learn as much as possible before you go for that interview. You need to show your potential employers your skills. You can do this by attending a hackathon or taking on personal projects and building your portfolio.
2. Fine-tune your Big Data, Computer Engineering, and Analysis skills
To become a Big Data Engineer, you need to be an expert in SQL, the foundational programming language of Big Data engineers. This is important because most of the data is in a relational database system. You will need SQL for querying data and SQL engines like Apache Hive for analyzing this data.
Apart from SQL, you also should have an understanding of programming languages that help with modeling and statistical analysis like Python and R. Expertise in Hadoop, Spark, and Kafka is important as well. Other than mastering the programming languages, you will need other key skills like how to use database architecture, find data warehousing solutions, construct data pipelines, utilize cloud platforms like AWS, data mining, and understanding of machine learning.
Data Management technology evolves constantly. This is why a Big Data Engineer must know about the current advancements of the field.
3. Get an entry-level job
Now, your first job doesn’t need to involve engineering. As long as it is related to IT, you will be able to gain valuable insights regarding how you can approach the challenges of data organization. During this job, you have to think creatively to find ways of solving problems. You will find that Big Data engineers don’t do everything by themselves. It is a collaborative field where you will have to work with data architects, data scientists, and management. In your entry-level position, you will be able to get a deep understanding of how the industry works in the real world. Also, you will learn how data is collected, analyzed, and used.
4. Pursue a Big Data course
If you want to advance in your field of Big Data Engineering, you must pursue industry-recognised Data Engineering courses. It will help in boosting your specific skills. There are so many options available. But, you have to choose one that is worth your time and will help you get a job that you want.
5. Pursue a higher degree in engineering, computer science, physics, applied mathematics or a related field
Now, most of the engineers are able to succeed without a higher education degree. But, with a master’s in computer science or computer engineering degree, you will be able to expand your knowledge, fine-tune your skills, and start working as a Big Data Engineer or a Data Scientist.
You won’t need a master’s degree for most of the jobs. Employers readily accept proof of technical expertise and relevant experience in place of a higher degree.
Related Post: Salary of a Big Data Engineer
Becoming a Big Data Engineer will give you an opportunity of collaborating with a diverse group of people. You will work closely with data modelers, architects, and other IT specialists for achieving different project goals. Pursuing a certification will not only help improve your knowledge but will also help you stand out from the crowd.