Companies can gather massive data, and they need the right technology and people to ensure that the data can be used properly by the time it reaches data scientists and analysts. Here is when data engineering comes to play. Data engineering is the practice of building and designing systems for storing, evaluating, and collecting data at scale. Working as a data engineer can give an individual an opportunity to make a difference globally where we will be developing 463 exabytes per day by 2025. Deep learning and machine learning fields cannot succeed without data engineers to channel and process that data.
Data engineers are responsible for maintaining, designing, and developing the data platform that includes data warehouses, data pipelines, data infrastructure, and data applications. Their ultimate goal is to provide companies with accessible data so that they can use it to optimize and evaluate their performance.
There are three vital roles that date engineers can fall into:
Small companies or teams typically have generalists where these engineers wear many hats as one of the few people focusing on data in the organization. They are often held responsible to manage and analyze data.
These engineers are often found in midsize organizations. Pipeline-centric data engineers require in-depth knowledge of computer science and distributed systems to work alongside data scientists to optimally use the data they collect.
Data engineers in larger companies focus on analytics databases. Database-centric engineers work across multiple databases and are responsible for evolving table schemas.
Some of the key responsibilities of these engineers are:
According to the National Association of Colleges and Employers, the average salary of a data engineer in 2021 is USD 119,158 per year which is pretty high when compared to salaries of software engineers or professionals working in the related fields. This is because demand for these engineers is high in number when compared to their supply.
With the right set of knowledge and skills to perform the mentioned roles and responsibilities, one can advance or launch a rewarding career in data engineering. Usually, students or professionals with a degree in computer science or a related field and work experience build a foundation of knowledge that is required in this quickly-evolving field. Besides, earning a degree there are several steps, which one can consider to excel in a data engineering career path.
A portfolio is often a key element in a job search as it shows hiring managers, potential employers, and recruiters what one can do. Adding independent data engineering projects to a portfolio website or even posting projects on LinkedIn profile project section or on sites like Github to set you apart from others.