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The amount of data which is being generated every day is putting IT engineers, managers as well as global leaders on toes. The enormous amount of data exchange, social media apps, and advanced technologies like Artificial Intelligence and Machine Learning are contributing towards this. While accessing the data was a challenge of the past, gaining it has become much easier today. However, the challenge remains to put this data to adequate use and generate meaningful insights out of it.
The size of data being generated today ranges to the tune of many petabytes. Organisations are understanding the power of this, still many of them fail to harness the complete potential of data sets in their disposal. This is leading to the creation of multiple new job roles like Data Scientists, Big Data Specialists, Data Mining Experts and Data Engineers. While people are familiar with most of these roles, the Data Engineering profile still remains a bit less explored.
A Data Engineer is someone who is liable for preparing data which can be further used for various kinds of analytical as well as operational uses. The importance of this role is on a rise and companies are now looking for candidates who have gone through a data engineer online course. They expect these candidates to sustain their business with changing market needs, and thus help in increasing revenue inflow.
Below in this article, we discuss key things about data engineering, what it is, how to become a professional in this field, and what is the career scope ahead. The key focus will be on how to become a data engineer in the first place, so have a look.
Who is a Data Engineer?
While a Data Scientist or a Data Analyst works on a data set and tries to figure out multiple things from it, a Data Engineer ensures that a data set exists in the first place.
- These are the professionals who maintain the complete data architecture and ensure that the flow of data is maintained between the servers and the applications.
- Data Engineers work on getting the dataflow process, integrating different applications to maintain this flow, and building pipelines to collect data at the nodal end. To build the pipelines, the most common method used by Data Engineers is ETL (Extract, Transform, Load).
- Their other essential work includes building data warehouses, where the collected data is stored, till the time it is retrieved by someone.
Data Engineer differs from Data Scientist in the sense that while a Data Scientist uses Statistics, Mathematics and Machine Learning models on a dataset, a Data Engineer works on managing the structure of the data, collecting it, storing it, and putting it for retrieval.
As we are now clear about what a Data Engineer role is all about, let’s discuss in detail about what all is required to become a professional data engineer.
Data Engineer Certification
The most crucial thing you need to possess to get selected into an organisation for a Data Engineering role is a degree or a certificate. Though the skills matter in the long term, it is the degree which certifies your experience in Data Engineer skills. Some of the best courses are mentioned below.
Post Graduate Program in Data Engineering
Simplilearn offers this course in collaboration with Purdue University and IBM, in an online bootcamp format. Students of this course get to learn concepts like Big Data, Hadoop, Spark, Azure, Data Engineer Capstone, Python, Java, etc. The course provides skills related to Data Visualisation, Real Time Data Processing, Data Pipelining, Big Data Analytics, Encryption, etc. Students are also provided placement support in companies like Amazon, Microsoft, HSBC, IBM, Deutsche bank, CISCO, Deloitte, etc.
Data Engineering and Smart Analytics
This course has specially been curated by Google to impart skills to students in the field of Data Engineering. The program material is aligned with other roles also, like Data Analytics and Database Engineering. The course is primarily divided into 4 parts and covers Big Data, Machine Learning, Serverless Data Processing, and fundamentals of creating and managing cloud resources.
Apart from these, there are various other courses which you can explore online. Not just online, some rare data engineering courses are also offered in offline mode as diplomas or postgraduate courses.
Data Engineering Skills
While the courses and certificates theoretically prove your expertise, it is necessary that you indeed possess some skills to benefit in the long term. The key skills required in a data engineer are listed below.
- Programming/Coding: Whatever the IT role may be, programming skills are an essential requisite. Some of the languages that you should know for this role are Python, Golang, Java, C++, MATLAB, Scala, Ruby, etc.
- Data Warehousing: The key role of data engineers is to collect data and store it somewhere until there is a need to retrieve that data and work on it. For this, they should know the concepts of Data Warehousing, which helps in creating repositories of data sets from different sources.
- Database: While managing and storing data, databases play a crucial role. Candidates should have familiarity with SQL and other database languages. They should also have experience of working on various related tools.
- Operating Systems: Knowledge of different operating systems like Windows, Linux and macOS is also important depending upon the project you are working on.
What are the Career Options for a Data Engineer?
Most computer science graduates run towards buzz-creating roles like Data Scientist, Data Analyst, Big Data Specialist, etc. This creates a very small competition for those who are genuinely interested in the field of data engineering.
- The average salary of a Data Engineer in India is ₹8,56,000 as per Payscale.
- The top companies to work for in this role include HP, Apple, NTT Data, Microsoft, IBM, Dell, PWC, Genpact, Chegg, etc.
- Some other related roles available are Azure Specialist, Data Consultant, AWS Data Engineer, etc.
The sector might not sound as booming as its counterparts, however, it is a very profiting sector with comparatively lesser competition. Therefore, budding data specialists should definitely give it a try.
