In this digital era, the success of any organization depends hugely on data. These days, companies collect a massive amount of data, commonly referred to as big data, to gain insights that lead to better decisions and business strategies. When such data is collected from different sources and analyzed, we can find answers to crucial questions like how to reduce costs or time to market and how to optimize resources and create sophisticated products. Big data is one of the most commonly talked-about career paths in the market.
A data engineer is a prominent designation in the field of big data, and you will find job portals filled with opportunities for this position. Such professionals discover and design algorithms to collect unprecedented amounts of data from disparate sources and improve raw data’s utility. They coordinate the collection, processing, and storage of large datasets. A seasoned data engineer is well-versed in using databases, ETL tools, data warehousing, big data concepts, cloud computing, and programming. No wonder professionals today rely on data engineering courses to gain these skills and step into the world of big data.
Are you aspiring to become a data engineer? Why not go through the rest of the article and understand what steps you can take to land a job as a data engineer.
Building a Successful Career as a Data Engineer
The demand for data engineers isn’t limited to one industrial sector. Currently, data engineers find employment opportunities in multiple sectors like banking and finance, IT, insurance, government agencies, agriculture, research, and healthcare. As companies continue to embrace digital transformation, this trend is expected to explore further in the years to come. So, look at the path that can lead you towards a data engineer career and make the most of the opportunities available out there.
Qualifications – The first thing people discuss in any job role is the educational background required for it. As far as a data engineer is concerned, there is no specific degree associated with this role. A bachelor’s or master’s degree in the field of mathematics can help you get started. A computer science or related stream is also suitable for individuals willing to switch into a data engineering domain.
Foundational Skills – You need to learn everything from scratch and lay the foundation with basic data engineering skills. Some of the introductory concepts include core math (linear algebra, calculus, probability, etc.) and statistics, data structures, programming skills in any language like Python, Java, R, or C++, and working on operating systems like Windows and Linux. A clear understanding of manipulating databases through SQL is also essential.
Intermediate Skills – After gaining the foundational knowledge, it’s time to take a step ahead and learn about big data applications. You can start with machine learning concepts in order to improve models and build more reliable data pipelines. Learn about data warehousing solutions like Panoply or Redshift to better evaluate massive data volumes. Next, you should know how to process big data in batches – using parallel processing with Apache Spark. When dealing with terabytes of data (or even larger), Spark is used as a unified analytics engine to conduct parallel processing tasks on clusters of machines. Hadoop was earlier used for this purpose, but Apache Spark outperforms it in many ways.
Big data tools – When you take the responsibility of a data engineer, a lot of advanced tools come in handy to make data ready for analysis. It is beneficial to be familiar with ETL tools like Xplenty, Talend, Oracle Data Integrator; Apache Hadoop-based technologies like MapReduce, Pig, Hive, HDFS, and HBase; and data modeling tools like Python, RapidMiner, KNIME, and Weka.
Big Data Certifications – When you have gained all the skills mentioned above, it is time to validate them through industry-recognized certifications. This is because you should have some proof to showcase your data engineering skills in front of employers. Some of the top big data engineering certifications you can consider pursuing are:
- Cloudera Certified Professional (CCP) Data Engineer
- IBM Certified Data Architect – Big Data
- Google Cloud Certified Data Engineer
- Associate Big Data Analyst (ABDA) by DASCA (Data Science Council of America)
- AWS Certified Data Analytics – Specialty
Is a Data Engineering Course Recommended?
The above steps may seem overwhelming for some aspirants, especially those who cannot dedicate too much time to self-study and prepare to become a data engineer. So, we would recommend you to take an online big data training course. A reliable training provider would include all the discussed skills in their curriculum and help you guide you step-by-step. Moreover, you can also prepare to pass the top big data certifications through these courses.
You would only need to enroll, and the training provider will give all the study materials. Accessing the video modules would only require a system connected to the internet. The syllabus is divided into short duration videos that are easy to incorporate into your busy schedule. So take up this opportunity to learn from industry experts and climb the big data career ladder.
Angela is a senior editor at Dreniq News. She has written for many famous news agencies.