Data engineers configure, fabricate, and upgrade frameworks of the collected data and process it in such a way that it makes sense while operating. They make data pipelines that are used by data scientists and associated authorities within the companies to develop more data-centric software that is optimized and more efficient according to the demand in the market. This IT job requires a combination of multiple tech stacks, which includes a thorough knowledge of databases, operating systems, and a bunch of programming languages.
To know more about the topic ‘Data Engineer Job Description’ let’s break the ice and proceed to see what is underneath. Before moving on to the different parts of the blog, check out the points that we are going to cover today.
Points to be discussed
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Who is a Data Engineer?
This is our very first section of the blog, in this we will cover the meaning of the data literate guys. In simple words, a data engineer refers to the person in an organization who is responsible for working on complex, unstructured, raw data and processing it in such a way that it is readable and usable by the groups associated with the data within an organization.
- They collect, manage, and manipulate the collected data from various sources.
- During the whole process of conversion of data to meaningful information, data engineers make it accessible to others.
- They work on the combined technology of data science and software engineering and also develop the software development life cycle.
- This structured processing of data creates a major difference in the organization, as raw data is not usable and because of this, it cannot be worked upon.
- Processing of this raw data provides analysis of raw facts and figures on which organizations can make an action plan for the future.
Alright, here we conclude our first section of the blog. In the upcoming section, we will see why we need these guys.
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Why Data Engineering?
Data engineering is a sub-domain of software engineering where the associated engineers work on the transformation and transportation of data to a highly usable format through pipelines to the associated groups in the organization.
Now, taking a deeper dive into why one should pursue this field, check out the below-mentioned points:
- There is a lack of data-literate candidates which creates a deficit in the availability of data engineers, therefore increasing the demand.
- It focuses on a scalable system that is data-centric and has a very strong architecture.
- It is the most demanded and fastest growing field nowadays as data is increasing exponentially.
- Data has become the most valued asset to organizations, it is a game changer now. Dependency on data has increased.
- Anyone who wants to grow should have a strong grip on the data, with the correct interpretation.
- Data can be used to get a brief whereabouts of the market on which further strategies can be made accordingly.
- As data is getting more complex, more complex technologies are introduced to handle it, and with these complexities, a trained workforce is required.
How to be a Data Engineer?
Following the below-mentioned steps, an aspiring data engineer can achieve great heights in the field just following the pointers and enjoy success.
- Earning a degree with technical background gives a kickstart to aspiring data engineers, a technical background is preferred.
- Huge experience as a data analyst also helps candidates to grab the opportunity.
- Should have a decent knowledge of data warehousing and data mining as through pipelines data is collected at a place for further processing.
- Building a portfolio in the said domain helps the aspirants to gather hands-on experience.
- Learning and mastering the needed skills by implementing the learned skill in real-world scenarios.
- Going on for the domain-specific certifications, as this authenticates the knowledge of aspiring data engineers.
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Skills needed by a Data Engineer
Welcome to yet another section of the blog, in this section of the blog, we will be answering two questions first one is ‘data engineer skills’ and the second one is ‘data engineer qualifications’. For the answers to these frequently asked questions, go through the below-mentioned points.
- As we know the education system and recruitment eligibility is evolving, and this evolution has leveled the playing field, success now more than ever depends upon the man and women with the right skill.
- Many organizations prefer candidates who are having a technical background specifically in computer science, it is advised you get yourself enrolled in any computer science degree course.
- A Master’s in the field is not necessary if you have the right amount of hands-on experience, but having one will your resume a higher chance to make a cut.
- Having a keen interest in coding, a data engineer should know how to do problem-solving.
- Having a basic understanding of statistics and machine learning also gives a push toward being a good data engineer.
- Aspiring candidates should be able to understand the basics of mentioned programming languages namely Python, SQL, R, Golang, Pearl, Ruby, and Scala.
- Having a good grip on computer fundamentals such as operating systems, databases, and system design.
- An individual with good analytical and critical thinking skills who can take the right decisions after evaluating the issues correctly and coming up with optimized solutions.
- Great communication skills and being a team player so that good collaboration can be established which focuses on better yields, and at last experience with the tools used by data engineers like Hadoop analytics.
Learn about the difference between a data engineer and a data scientist in our blog on Data Engineer vs Data Scientist!
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Data Engineer: Roles and Responsibilities
In this section of the blog, we will answer one of the most commonly asked questions ‘what does a data engineer do’, let’s discuss the work of data engineers in an organization:
- They have to acquire the data collected through various sources, form datasets, and prepare it according to the need of the organization.
- Based on the company’s objective, they have to develop optimized algorithms per the organization’s needs.
- The prepared algorithms and APIs are also embedded by them in the software being developed.
- They have to research the collected data to come up with an analysis that has meaning.
- Development of optimized machine learning prediction models with high accuracy to give better yields.
- Maintenance and creation of the database architecture for accurate functioning of manual functions.
- They have to write scripts needed for the automation of the systems to save the time and resources of the company for data processing.
- Generalist Data Engineer – While working in small teams, generalist data engineers focus on the process of data inclusion for further processing.
- Pipeline-centric Data Engineers –
- They work in collaboration with other data-associated teams on more complex acquired data to transform the raw collected data and make it more readable and accessible.
- They work in larger teams as compared with generalist data engineers.
- Database-centric –
- They work in a very large team for bigger organizations that have more data to handle.
- They handle the database schemas.
Whoa! That’s too much for a role in the industry but you will be delighted to know that your pay package is also too much, have a look over the next section we will prove it to you.
Career Perspective and Salary Expectations
This is the most awaited section by most of the guys don’t you think? I bet on the same because you guys will be grinding yourself to be the guy in the industry and be wondering what I would be getting for this much hard work. Have a look over the below-mentioned points to get an insight into everything.
- Data Engineer jobs are among the highest salary-paying jobs. The average data engineer salary in India is around ₹10 LPA and their salary ranges from ₹5 LPA to ₹15 LPA.
- The estimation of the average salary is done based on the feedback received from different organizations.
- While talking about the world, the average salary expected for a data engineer is over $100,000.
- The growth rate expected in the field is around a 50% hike in a year-over-year turnover.
- The position is well in demand, data engineers will stay in demand till the time data exists.
- The job of data engineers has been leading the trending jobs pages since 2019 till now.
- Data engineer skills play a vital role in deciding their pay package. They can expect an average salary of ₹9 LPA.
By now you have seen everything needed to be in the industry, only the last thing is left now, that is the conclusions that can be drawn.
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Conclusion
The job of data engineers is high in demand, no matter how far technology goes, data will be around forever and will become more important as time passes. Their job is all about dealing with the data and scalability of the associated system. They always have to stay updated with the latest technology around and keep brushing up on their skills. If an individual is thrilled working on many technologies and at the same time earning well, the job of a data engineer is for you.
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