The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching 64.2 zettabytes in 2020. Over the next five years up to 2025, global data creation is projected to grow to more than 180 zettabytes.
Big data is transforming the way business can be optimized. Leveraging data can empower organizations with innumerable benefits, provided the data is of good quality and competent to perform complicated tasks. Over the passage of time, the management of data has become more significant.
It is, indeed, a technological art and science, to extract such huge volumes of data, validate it, manage it, and make the most of it for further use. That is where the role of a data engineer comes into the picture.
Let us understand what data engineering means and what roles does a data engineer play in maximizing the benefits of data.
Data engineering is the science to collect and validate information so that it can be leveraged by data scientists. It focuses on creating systems to manage the collected information, in almost all major industry segments. It is a software engineering approach to design and develop different information systems.
Data engineering is designed to support the process of data management so that analysts, data scientists can utilize the data with security, accuracy, and swiftness. As the name suggests, data engineering looks at the engineering part – designing and building pipelines for data transformation and transportation so that when it reaches the data scientists, it is in a highly functional form. These pipelines are supposed to collect data from various sources and assemble them into a single data warehouse to showcase the data with uniformity.
And the resources that perform data engineering to their best are the data engineers!
Data engineers are the human resources that are responsible for effective data engineering practices in any organization. They create data reservoirs and help in the management of those reservoirs by developing, testing, and maintaining databases and processing systems. They install pipelines that carry the sorted information that data scientists can extract for their further course of action.
Data engineers play an important role in understanding the objectives of any business and then aligning data with these objectives, by handling complicated databases and datasets. Based on this understanding, they create algorithms that can offer organizations access to necessary data, in a usable format.
It is tricky to understand the difference between a data analyst, data scientist, and data engineer. It looks as if they all deal with data and perform the same jobs. But it is not true. Each of them has their own designated set of tasks to be executed.
A data engineer is involved in various activities, some of them are as below:
There is so much data everywhere, that can be leveraged for better business opportunities across all workflows in the organization. Technologies that pertain to data handling are complex and need a certain skill to be managed in the best way possible. As the data gets more complicated, newer technologies come around to help get the exact value from the information heaps. That is where a data engineer can be of most help.
Pursuing a career in data engineering can prove worthwhile in terms of offering value addition to the organizational success, easy access to data, and great assistance to decision-makers in terms of offering them data in their desired format, at their desired time. Now that most companies have undergone a digital transformation and technologies like IoT and AI are taking over, the availability of heaps of data is quite evident and hence taking up the role of a data engineer is quite fruitful.
The world is moving towards BI and Big data. Data engineering is helping these technologies to connect increasingly with masses, offer well-governed data pipelines and extract the best possible output. Therefore, data engineers are in heavy demand and an increasing number of developers are trying hard to achieve all necessary skills to become a good one.
Yearning to become a data engineer is one topic, but how to become one is what matters most. Here are certain key steps that must be taken to ensure that you become a successful data engineer:
Generally, there are three major roles that are earmarked for data engineers:
Generalists – usually found in smaller teams in which data engineers are supposed to perform many data-centric jobs.
Database Centric – Found in larger teams in which data flow is a major activity and data engineers must have a higher focus on analyzing multiple databases with data warehouses.
Pipeline Centric – Found in a middle business segment where data engineers are supposed to work synchronously with data scientists to make the most of data.
Here are the multifaceted data engineer responsibilities that are expected to be performed by the task force:
Data engineers must possess the necessary skills that can help them perform their best and make organizations leverage their best potential:
According to payscale, the average data engineer salary is $ 92,496 per annum. An entry-level Data Engineer with less than 1-year experience can expect to earn an average total compensation of $77,300. An early career Data Engineer with 1-4 years of experience earns an average total compensation of $87,822. A mid-career Data Engineer with 5-9 years of experience earns an average total compensation of $103,616. A senior data engineer salary, with 10-19 years of experience is around $117,902. In their late-career (20 years and higher), employees earn an average total compensation of $115,411.
According to indeed.com, the average salary for a data engineer is $128,607 per year in the United States and a $5,000 cash bonus per year.
According to glassdoor.com, the national average salary for a Data Engineer is $112,101 in the United States.
According to salary.com, the average data engineer salary in the United States is $108,473 as of June 28, 2021, but the salary range typically falls between $90,615 and $126,346.
Data engineering is soaring high and there are newer trends that are coming up. Here is a peep into the possible futuristic trends that data engineers would enjoy, in their upcoming ventures:
Here are some of the frequently asked interview questions for the position of a data engineer:
Data is omnipresent and forms the crux for any organization to succeed. BI and Big Data are the pioneering technologies that can offer the best of out these heaps of data. For the globe surrounded by data, business intelligence and analytics serve to be the front face of information in desired formats and layouts and data engineers are the ones playing their roles with complete efficacy.
It is these data engineers because of whom the raw data reaches the data scientists in its best, usable form. The future has a lot in store for data engineers and its associated trends!
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