The world of data science is evolving at a very fast pace. Data used to be readily available in a single database, and all data scientists needed was enough Python skills to build simple scripts.
But over time, we’ve come to learn that data grows, with growing companies inevitably adding more data sources. Data streams in batches of terabytes accumulate really fast. For this reason, companies are hiring data engineers to help manage, process, and assess data.
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What Does the Job of a Data Engineer Involve?
Data engineering involves designing and building data infrastructure for collecting, storing, and analyzing data. Data engineers manage and transform raw data into high-value information for business analysts to access and utilize.
Data engineering is a wide field that has potential applications in just about every sector out there. Given its importance, data engineers are in high demand for their skills in mining and querying data.
If you’re interested in becoming a data engineer, here’s a brief guide on how you can gain the expertise and fine-tune your data science skills to become a professional in this field.
1. Earn a Degree in a Data-Related Field
Most data engineers have a bachelor’s degree in relevant fields like math, statistics, or computer science to create a strong foundation for their careers. Make sure you excel on courses involving computer science, database management, coding, or data structures and algorithms.
This will enable you to understand the basic concepts of data engineering so you can get an entry-level job where you can get real-world experience.
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2. Fine-Tune Your Data Engineer Skills
You need to master your data management and assessment skills, especially when it comes to big data. Some of the skills you can hone, for example, include:
- Coding: You need to be proficient in coding and programming languages such as R, Python, Scala, Java, and SQL.
- Using ETL Systems: ETL, or extract, transform, and load systems, is the process by which you’ll transfer data from databases to a single repository such as a warehouse. Some of the tools you can familiarize yourself with include Alooma, Stitch, and Xplenty.
- Data Security: While many companies have several departments solely focused on data security, you might find yourself at a job where you’re tasked with securely managing and storing data to protect it from loss or unauthorized access.
3. Earn Some Certification
Getting certified will not only help you develop your skills and expertise as a data engineer, but it will also make you a very appealing hire to potential employers. You’ll find that some job listings require applicants to have undertaken a particular certification course.
Some of the courses you can consider include the IBM Certified Data Engineer, Google Cloud Certified Professional Data Engineer, Data Coach, or the Cloudera Certified Professional Data Engineer.
Winding It Up
Data is everywhere, and it would not be overselling the field by saying that big data is the new oil. Data engineering is a strategic function with many tasks such as constructing predictive models, high-performance algorithms, as well as data mining and management.
As such, the job of a data engineer is crucial for an organization to realize its full potential. Consider the tips highlighted above to kickstart your career as a data engineer.