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 with 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 learn more about this in-demand profession.
Who is a Certified Data Engineer?
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 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 focus on Machine Learning and Advanced Statistical Modeling.
- Data Analysts are saddled with the responsibility of interpreting data to develop actionable insights, and to develop, test, and maintain data management systems, including large-scale processing systems and databases.
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 in which 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.
Hevo’s No-Code Data Pipeline is an invaluable asset for anyone pursuing a data engineering certification. With its intuitive platform, you can efficiently manage data workflows and enhance your learning experience. Let’s see some unbeatable features of Hevo Data:
- Live Support: With 24/5 support, Hevo provides customer-centric solutions to the business use case.
- Fully Managed: Hevo Data is a fully managed service and is straightforward to set up.
- Schema Management: Hevo Data automatically maps the source schema to perform analysis without worrying about the changing schema.
- Real-Time: Hevo Data works on the batch as well as real-time data transfer so that your data is analysis-ready always.
Get Started with Hevo for Free
Skills Required for a Certified Data Engineer
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.
Top 7 Data Engineering Certifications in 2025
Google Professional Data Engineer
- Focus Areas: Data processing, machine learning models, data security, and operationalizing machine learning.
- Benefits: Validates skills in managing and processing data on Google Cloud Platform, leveraging machine learning, and designing data solutions.
- Skills: Data pipeline creation, database management, machine learning, and data warehousing on GCP.
- Cost: $200 USD
- Register: Professional Data Engineer
AWS Certified Data Analytics – Specialty
- Focus Areas: Big data services on AWS, including data lakes, data warehousing, data processing, visualization, and security.
- Benefits: Recognizes expertise in AWS big data services like AWS Glue, Amazon Redshift, and Kinesis, supporting roles in data engineering and analytics.
- Skills: Building and managing big data solutions, using AWS analytics services, and optimizing data lakes.
- Cost: $300 USD
- Register: AWS Certified Data Analytics
Microsoft Certified: Azure Data Engineer Associate
- Focus Areas: Data storage and management, data processing and transformation, data security, and Azure services like Synapse and Databricks.
- Benefits: Demonstrates proficiency in implementing and managing data solutions using Azure services, suited for cloud-based data engineering roles.
- Skills: Data integration, data transformation, data storage solutions, and performance tuning in Azure.
- Cost: $165 USD
- Register: Azure Data Engineer Associate
Databricks Certified Data Engineer Associate
- Focus Areas: Apache Spark and Databricks environment, data ingestion, transformation, and production data workflows.
- Benefits: Validates capabilities in working with big data processing on Databricks, especially suited for roles requiring Spark expertise.
- Skills: Data engineering on Spark, data ingestion techniques, ETL, and real-time data processing.
- Cost: $200 USD
- Register: Databricks Certified Data Engineer Associate
IBM Certified Data Engineer – Big Data
- Focus Areas: Big data processing, Hadoop and Spark, data storage and management, data security, and IBM big data tools.
- Benefits: Certifies knowledge in managing large datasets, processing big data, and using IBM tools in big data environments.
- Skills: Hadoop ecosystem, Spark, ETL processes, and big data analytics.
- Cost: $200 USD
- Register: IBM-certified data engineer
Cloudera Certified Data Engineer (CCDE)
- Focus Areas: Apache Hadoop, Apache Spark, data pipelines, and data processing workflows within the Cloudera ecosystem.
- Benefits: Recognizes proficiency in building and managing scalable data engineering solutions using Cloudera’s big data platforms.
- Skills: Data processing with Spark, building ETL pipelines, handling Hadoop clusters, and managing data workflows.
- Cost: $295 USD
- Register: Cloudera Certified Data Engineer (CCDE)
Snowflake SnowPro Core Certification
- Focus Areas: Snowflake architecture, data loading and transformation, data security, query performance optimization, and monitoring.
- Benefits: Demonstrates expertise in working with Snowflake for cloud data warehousing, ideal for cloud-focused data engineering roles.
- Skills: Data warehousing in Snowflake, SQL for Snowflake, performance tuning, and data security best practices.
- Cost: $175 USD
Register: SnowPro Core Certification
Salary of a Certified Data Engineer
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
- Before you start the Data Engineering journey, you must remember 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 should also 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
- 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 machine learning algorithms, 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 is 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 into a target Database.
Integrate your Source to Destination Effortlessly!
No credit card required
5) Familiarity with Multiple Operating Systems
- Different industries today use different Operating Systems 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 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, give 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 of 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 firsthand.
FAQs
1. How much does a Google Certified Data Engineer make?
A Google Certified Data Engineer typically earns between $100,000 to $150,000 per year, depending on factors like experience, location, and the specific company they work for.
2. What degree do you need to be a data engineer?
While a bachelor’s degree in computer science, information technology, or a related field is commonly preferred, relevant experience and certifications can also help candidates secure data engineering roles without a formal degree.
3. Are there any prerequisites for data engineering certifications?
While many certifications have no formal prerequisites, having a foundational understanding of data management, programming, and cloud platforms is beneficial.
Samuel is a versatile writer specializing in the data industry. With over seven years of experience, he excels in data science, data integration, and data analysis, crafting engaging content on these topics. He is also adept at WordPress development. Samuel holds a Bachelor's degree in Computer Science from Lagos State University.
