In today’s “Information Age“, data acts as the driving force for all those companies which rely heavily on technology. Following the massive evolution in data technology, the demand for Big Data professionals has been on the rise. According to Forbes, “Machine Learning Engineers, Data Scientists, and Big Data Engineers rank higher among the top emerging jobs on LinkedIn”. This implies that people who have the skills to handle and manipulate data are in high demand.
Data Engineers are the first set of people to tackle the influx of structured and unstructured data that enters an institution or company’s systems. This means that being a Certified Data Engineer in the current technological landscape involves building efficient systems that can process, store and analyze data at large scales.
Organizations are collecting huge volumes of data regularly and Data Engineers are needed to ensure that this data is consistently transformed in the form required by the company.
This article will provide you a detailed description of the work and importance of a Certified Data Engineer. Furthermore, it will take you through the skills and knowledge areas in which you should be well prepared to excel in this role. Read along to know more about this in-demand profession.
Table of Contents
Who is a Certified Data Engineer?
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Data engineers are IT professionals who primarily prepare data for Operational and Analytical uses. In other words, Data Engineers are responsible for building and maintaining Data Pipelines and Data Warehouses that house Big Data in such a way that allows data to be accessible later on.
Data Engineers work concurrently with Data Architects, who work to manage data systems and understand a company’s data use; Data Scientists, who focus on Machine Learning and Advanced Statistical Modeling; and Data Analysts, who are saddled with the responsibility of interpreting data to develop actionable insights, to develop, test, and maintain Data Management systems, including large scale processing systems and Databases.
Hevo Data is a No-code Data Pipeline that helps to transfer your data from 100+ sources to the Data Warehouse/Destination of your choice to visualize it in your desired BI tool. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also takes care of transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
It provides a consistent & reliable solution to manage data in real-time and you always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using a BI tool of your choice.
Check out Some of the Cool Features of Hevo:
- Completely Automated: The Hevo platform can be set up in just a few minutes and requires minimal maintenance.
- Real-Time Data Transfer: Hevo provides real-time data migration, so you can have analysis-ready data always.
- 100% Complete & Accurate Data Transfer: Hevo’s robust infrastructure ensures reliable data transfer with zero data loss.
- Scalable Infrastructure: Hevo has in-built integrations for 100+ sources that can help you scale your data infrastructure as required.
- 24/7 Live Support: The Hevo team is available round the clock to extend exceptional support to you through chat, email, and support calls.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Live Monitoring: Hevo allows you to monitor the data flow so you can check where your data is at a particular point in time.
You can try Hevo for free by signing up for a 14-day free trial.
Importance of a Certified Data Engineer
The popular buzzword – “Big Data” is not new anymore, you must have heard people talk about it and other keywords like Data Science, Data Engineering, etc. on different occasions. Now, a question comes to mind, Is it really worth it to invest your time in training to be a Certified data Engineer? The answer is YES.
Start with the increasing demand for Data Engineers. For you to be motivated to invest your time and resources in training to be a Certified Data Engineer, there must be a high demand in the industry you are about to venture into. The IT industry is evolving really quickly and the need for Data Engineers is on the rise.
You can have not realized the fact that we all generate data in our world today. Even as we sleep, we all generate data through our mobile phones and computers. So you can imagine the amount of data present in the world as a whole, and the need for more Certified Data Engineers.
Another reason is the fact that data is used in every industry in our world today. This is to let you know that Data Engineers and other data professionals are not limited to just a few industries. Information Technology, Finance, Manufacturing, and Automobiles are some of the prominent industries where Data Engineers are in huge demand.
In the same vein, training to become a Certified Data Engineer is really worth it in the sense that once you are Certified, it provides you a competitive advantage. Data-driven decision-making is a key ability of Certified Data Engineers, and when you make these kinds of decisions, you are purely making decisions based on the analysis of data rather than instinct.
Skills Required for a Certified Data Engineer
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A Certified Data Engineer needs to be on edge with a wide range of technologies and Machine Languages. Also, not only should a Data Engineer be comfortable with a lot of languages, he should be able to deploy each language for specific reasons when the need arises.
However, the following skills are expected as a must in a Certified Data Engineer:
- Knowledge of Database Architecture and experience in Data Warehousing
- Knowledge of developing fully functional large-scale applications
- Proficiency in a wide array of programming languages, especially Python, R, Java, C/C++, MatLab, Ruby Perl, and SAS
- Proficiency in Operating systems, especially Linux and Unix
- Database solution languages
- Splitting Algorithms and Distributed Computing
- Working knowledge of Regression Analysis and a good grasp of Statistical Modeling
Of course, a Certified Data Engineer must have certain technical capabilities, but the list is not limited to the above skills and much of the job rests on the ability to make Data-driven decisions.
To know more about the specific skills required for a Certified Data Engineer visit here.
Salary of a Certified Data Engineer
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Your interest in a job should not only be as a result of the salary but at the same time, there is no denying that salary is also essential. As of July 2021, the average annual pay for a Data Engineer in the U.S. is 120,000 Dollars.
It’s no surprise as to why Data Engineering skills like Python, Shell, SQL, and others, rank higher among the highest-paying skills in the world today. Not only is there a large demand for Certified Data Engineers, but the demand also keeps increasing every day.
Excelling as a Certified Data Engineer
To become an excellent Certified Data Engineer, you need to obtain the following:
1) Strong Programming Background
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Before you start the journey of Data Engineering, you must keep in mind that Data Engineers are at the interface of Data Science and Data Engineering. You are required to acquire the necessary skill set, as you’ll have to first become a Software Engineer.
However, you need to be very good at programming to start with. You must be good with Scala and Python and also should be able to create software applications with them, as those two programming languages are primarily the technologies around which the Data Science world revolves.
2) Working Knowledge of Machine Learning
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Machine Learning is a branch of Artificial Intelligence that allows machines to learn without explicit programming. To have a competitive edge as a Certified Data Engineer, you must have an elementary knowledge of various algorithms of Machine Learning, as this will assist you in creating efficient pipelines for data generation and data collection. Python is a technology often used to design Machine Learning algorithms.
3) Deep Understanding of Databases
To become a Certified Data Engineer, you need to also understand your Databases. You can start by learning SQL and its basics. SQL is a well-established and declarative language that describes what to do.
Also, you need to learn how to model data and in this same vein, learn how to work with less structured data, because you may find yourself in a situation where the data is not presented in a structured way.
4) Efficiency in Data Processing
Why do you need to master Data Processing techniques? The main reason being that you can get data from several sources, which you then need to process and integrate for further use. Furthermore, you should learn how to process Big Data in batches and streams so you can load the result in a target Database.
5) Familiarity with Multiple Operating Systems
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Different industries today have different Operating Systems they use based on wants and preferences. While some may prefer to work on Linux, other industries may like to work on Windows and so on. Therefore, to become a Certified Data Engineer, you must familiarize yourself with using different Operating Systems.
6) Certified Training
It is difficult to become a Certified Data Engineer in today’s world especially if you are new to this field. Becoming a Data Engineer demands a strong and in-depth knowledge of technologies, tools, and a strong work ethic and will to learn.
One of the steps to take towards becoming a Certified Data Engineer is getting the right training. There are lots of courses on the internet that you can enroll in and get yourself Certified. Getting Certified in your Data Engineering career pursuit will, no doubt, hand you a competitive edge in the industry.
7) Experience
Another easy way to become a Certified Data Engineer is to gain entry-level job experience. You can achieve this by seeking out IT assistant positions where you learn or in a small company. Enhance your programming and Software Development skills, as a strong grasp of multiple programming languages, will be essential to kick start your career in Data Engineering.
Ensure you gain more experience, and as you do that, solve real-world problems. This will support you in convincing a potential employer that you have the skills and experience to be the right Data Engineer for their data needs.
Future of Data Engineering
The future of Data Engineering is clear. As Data Science becomes increasingly more prevalent, so does the need for Data Engineering become increasingly significant. For every exciting development we hear about, there is usually a Data Engineer behind it. For example, autonomous cars are becoming significantly widespread and will soon be the new norm in our present world.
Therefore with the evolution in technological trends, the demand for Data Engineers will only continue to increase.
Conclusion
This article explained the various important aspects that you need to consider before pursuing Data Engineering as a career. It discussed the work you will do and the salary that you may need to How to be a Certified Data Engineer. Also, the article elaborated on the skills that you need to master before you can compete for this role in the current scenario.
A huge part of your work as a Certified Data Engineer involves collecting data from multiple sources and integrating the incoming data into the desired form. This cumbersome process can be simplified by using Hevo Data which provides an automated Data pipeline that will take care of your data collection and ETL processes. Furthermore, it allows you to transport data from various sources of your choice to the Data Warehouse like Amazon Redshift, Snowflake, etc.
Want to take Hevo for a spin? Sign up here for a 14-day free trial and experience the feature-rich Hevo suite first hand.
Samuel specializes in freelance writing within the data industry, adeptly crafting informative and engaging content centered on data science by merging his problem-solving skills.