Why data engineering skills are essential for a software engineer for entry-level resources
Over the past decade, the data field has evolved so drastically that now it is at its peak. Big data is crucial to everything that is being done by companies and businesses. As organizations grow, more and more data gets added each day. A leading IT company stated that around 2.5 quintillion bytes of data are generated every day. Big data is growing so fast that organizations are not able to keep up with it. Additionally, the emergence of cloud-based warehouses and scalable processing means that not only data is collected frequently; it is also processed frequently and made accessible to all across an enterprise. All these data processing systems and solutions require sophisticated architecture which leads to the need for competent data engineers.
The massive growth of the data field, the available tools, the occurring challenges in an evolving market, and the right solutions to meet those challenges may seem to be general in an aerial view but when it comes down to each company, it drastically differs in scale and deployment. Data is an important part of Information Technology and there is a need for skilled resources. Having said this, it is equally important to realize that skills do not come up on their own and need to be honed, the earlier the better. Many businesses look for fresh minds that can be trained to keep in pace with the evolving IT industry. However, with the hundreds of engineers graduating each year, a pre-existing skill set will be quite beneficial. How beneficial can it be? Read on to find out.
How to get an edge ahead of others when you are a fresh engineer?
It is true that to gain experience, one needs to work in a particular field for a while. Yet, one cannot refute the fact that additional knowledge can help greatly even when starting at an entry-level. Multiple courses provide insight into a specific field that would benefit the one taking it. Courses focused on data engineering help a student learn a lot even as a fresher.
Not only does data engineering have great potential right now, anyone who knows data engineering especially at an entry-level will stand out among the crowd. This stand out is not in general terms but means standing out with the skills that are in high demand right now. It is such people that companies hunt to add to their workforce. Since there are many fields available now, why is the focus on data engineering? Does data engineering truly have more potential than other fields? Read on to find out.
Why choose data engineering?
In the last 10 years, many companies have started on the journey of digital transformation and have successfully completed it. This journey has produced large volumes of data, new and complicated with a higher frequency rate. To organize such large volumes of data and to ensure its security, availability, and quality, there is an urgent need for data engineers now. It is clear that with the emergence of corporate digital transformation, IoT (Internet of Things), and the turnover to become AI-driven, businesses need data engineers to complete their data science goals and initiatives. The role of a data engineer keeps growing in importance as companies need people solely to process data in a way to extract maximum value from it quickly.
Many companies are now investing in AI and analytics models to stay competitive in the IT market. With the size of data increasing day by day, scalability has become equally important. Hence, data engineering has a lot of potential right now.
What are some skills in demand right now?
At present, companies are looking for employees with skills that will help them in their digital transformation journey. Talking about data engineering specifically, here are some skills and sub-skills required by companies in the IT field.
- Knowledge of programming languages: At basic, knowledge of python is required. Other than that, knowing Java, Hive, Presto, R, and Scala might be necessary when it comes to building data pipelines.
- Knowledge of Analytics/BI Tools: This knowledge is necessary when building a data pipeline that supports machine learning and data analysis.
- Knowledge of Operating Systems: Knowing all about networks, server management, Windows, UNIX-based systems, LINUX, and virtual machines is necessary.
- Knowledge of Cloud: Since most companies and their external data suppliers store data on-premises and on the cloud, knowing how to bring all data together for usage is vital.
- Knowledge of Optimization: Knowing how to build a data pipeline is important as well as knowing how to make it efficient and scalable. Knowing to design, build, and to optimize performance is necessary.
- Knowledge of Database Management: Thorough knowledge of database tools and languages is vital. Not just NoSQL and SQL knowledge but also advanced DBMS knowledge and skills are needed.
- Knowledge of DevOps: Companies are looking for developers who have the mindset and skill set of playing the Ops role efficiently.
- Knowledge of Domain and Business Expertise: Each company’s data contains a lot of business information. Knowing the business domain is necessary to work as per the business strategy.
Though this list may seem tedious, yet all these skills and knowledge are what IT companies are expecting from their workforce. Companies are on the lookout for resources with these skills, and a fresher having the same skill set would be quite beneficial for the company and the person. So, is there any scope for entry-level engineers?
What is the scope for entry-level data engineers?
Data engineering jobs is one of the most in-demand jobs in the market. At an entry-level, the company may focus more on skills rather than experience. That is why any additional courses or internships in data engineering hold value. An entry-level data engineer will also get to learn a lot by working along with experts in the same field that will count later as valuable experience.
Most companies now hire people with extra skill sets rather than hire different people for different skills. IT companies prefer to hire people with pre-existing skills so that they can hone their skills and train them to be experts. Some freshers who took up data engineering courses have landed their first jobs in big companies as entry-level data engineers. Being a software engineer has become common; having data engineering skills is what is in need now.
Beyond entry-level: What the future holds?
In India, the demand for data engineers is rapidly rising as all companies are walking on the path of digital transformation. Just as how farmers maintain their fields well, cultivate the soil, harvest the crops, prepare the crops so others can utilize them well, similarly data engineers prepare, process, and maintain the data well so that companies can use insights derived from data to make value-driven business decisions.
It means that a data engineering job will only grow and broaden out in the days to come. A data engineer will always keep learning and expanding the data engineering skills to match the pace the IT industry is rolling forward. This pace results in a stable career despite economic or financial upheavals in society. A profession that is in demand as well as the foundation to build a bright future would be the right profession.
How can AptusLearn help you?
AptusLearn offers a Professional Certificate Course in Data Engineering on Cloud Platform. This course is a 6-month weekend course to help one become an expert in data engineering, cloud computing, DevOps, and cloud programming. This advanced course helps one understand data platforms; use architecture framework in AWS cloud platform, and acquire experience in modern distributed data analytics. Utilize this course to gain data engineering skills and start a well-founded career. For more information, please check