In today’s digital age data science is a buzzword in the IT world. It is helping us in many extraordinary ways, from helping cars drive themselves to help Facebook tag you in photos. Data engineers are very important people of any enterprise data analytics team. They are the professionals who build pipelines and transform the data into the formats that data scientists can use. They are responsible for optimizing, managing, overseeing, and monitoring data retrieval, storage, and distribution within the organization.
Data engineers can find trends in huge data sets and also can develop algorithms to help make raw data more useful to organizations. For this, they require a significant set of technical skills which include a good understanding and deep knowledge of SQL database design and multiple programming languages. They also need good communication skills to work together with other departments to understand what business leaders want to gain from the large datasets. They always try to give easier access to raw data so they need to understand the client’s or company’s objectives.
It is crucial for data engineers to have business goals in line when working with data, especially for those who are working with large companies that are handling complex and large datasets and databases. People who want to land their career in the field of data are seeking the best data engineering courses and gaining the required skills.
Let us know more about the roles and responsibilities, salaries, and the demand of data engineers in the IT landscape.
Roles And Responsibilities of Data Engineers
Larger organizations often have multiple data scientists and analysts to help understand data while medium and small companies rely on a data engineer to work in both roles. So a data engineer plays a vital role in any company and they are responsible for a variety of work they do. Some of their roles and responsibilities are mentioned below.
The Data Engineer Role- There are three main roles that fall under the umbrella of data engineers.
- Generalist- This job role is found in small teams or small companies. These data engineers as generalists are responsible for the steps for a data process, mining and data analysis. This role suits those who want to switch from data science to data engineering.
- Pipeline-Centric- This role is found in midsize companies. These data engineers work with data scientists to make use of the data collected. They require in-depth knowledge of computer science and distributed systems.
- Database-Centric- This job role is often found in larger organizations where the flow and managing of data is a full-time job. Database engineers work with data warehouses across multiple databases and can develop table schemas.
Data Engineer Responsibilities- Data engineers are tasked to keep their eyes on inconsistencies or out for trends that can affect business goals. Their main responsibilities are managing and organizing data. As it is a highly technical job role, it requires skills in areas such as mathematics, programming, and computer science. Mentioned below are some of the most common responsibilities of data engineers.
- Develop, create, test, and maintain architectures.
- Align architecture with business needs.
- Data acquisition
- Develop and manage the data set process.
- Implement programming language and tools.
- Identify ways to improve data reliability, quality, and efficiency.
- Conduct research for business and industry questions.
- Use large data sets to solve business problems.
- Deploy statistical methods, machine learning, and sophisticated analytics programs.
- Prepare data for prescriptive and predictive modeling.
- Find hidden patterns using data and techniques.
- Use data to discover tasks that can be automated.
- Deliver insights and updates to stakeholders based on data analytics.
- Communicate data trends to others within the organization.
Demand And Salary for Data Engineers
A career in data engineering sounds quite right for those who are having a keen interest in numbers, data, and technology as there is a prediction by Gartner that 2021 is going to be the year of hyper-automation, and the way to start is by driving insights from the huge amount of data organizations have. That is where the need and demand of data engineering professionals come into the picture and it is the reason the field of data engineering is rapidly growing.
So several organizations big and small, established and new players in the market, are seeking skilled professionals and are ready to pay hefty data engineering salaries and growth opportunities. According to DICE’s 2020 Tech Job Report, Data Engineer is the fastest-growing job in 2019, growing by 50% YoY. Data Scientist is also up there on the list, growing by 32% YoY. We can understand it with the following image.
There are several factors that can affect the average salary of data engineers such as skills, country, industry, experience, size and type of organization, academic education and training too. Their salary averages vary from source to source and are based on the U.S. market and before taking out taxes. Glassdoor estimated the average base pay for data engineers at $102,864 per year. This report is based on earnings reports provided by thousands of companies. So it’s a pretty good cash amount for data engineers.
On the other side, the job aggregator and information site Indeed.com reports higher earnings for data engineers $129,415 per year with a possible $5,000 bonus.
Another source is STACK OVERFLOW which has over 50 million daily users and creates a well-known survey summarizing the latest IT trends. They reported that the average data engineer salary is around $92,160 per year.
So it is clear that earning as a data engineer is quite worthy and you can make over $100,000 in your current job. And if you earn less try to get new opportunities to catch one of the biggest waves in the labor market as it is the golden time to choose a career as a Data engineer.