Data Engineer is one of those titles that are both highly coveted and highly misunderstood. Data engineers are responsible for gathering all the data in the world and processing it for human use. They work with computers, so you can think of them as the person who feeds the data into the machine. The data they gather is vital to the success of the whole operation. In a software company, the data engineer could be the one who feeds the data into a customer's website. In a company that deals with health data, they could be the one who feeds the data into a medical system. However, there is more to it than that.
What Is A Data Engineer?
Data Engineers are the software engineers of the data world. They write software to extract, store, manage, clean, and use data. They are experts at how to extract, analyze, and visualize data. Big data specialists DSStream, say that the job of an exemplary data engineer is to make sense of complex information and turn it into usable information. A data engineer is a critical developer in the big data and analytics ecosystem. They are the bridge between information and action.
What Do They Do?
A Data Engineer is a person who works with computer code to gather, organize, and analyze data and to design, create, and maintain computer software and hardware for data processing and analysis. A data engineer is also ideally familiar with and has a good understanding of the following:
– How to use and modify computer programs to perform automated data analysis tasks.
– How to design and implement hardware and software systems and features to meet data processing and analysis requirements.
– How to analyze, interpret, and modify data through an engineering process.
Differences Between a Data Engineer and a Data Scientist
The critical difference between these two disciplines is that data engineers focus on the infrastructure while data scientists perform data analysis. Nevertheless, there is some crossover between the two.
– Advanced mathematics and statistics.
– Machine learning.
– Advanced analytics.
– Advanced programming.
– System distribution.
– Data pipelines.
They both tend to deal with:
– General analysis.
– General Programming.
– Big data.
How Do You Become A Data Engineer?
Now that you know how these two jobs differ, you may wonder how to go about getting one as a data engineer. Data engineers are tasked with developing the systems, software, and techniques that enable organizations to extract value from data. This is a rapidly evolving field, and data engineers are expected to keep pace with the rapid pace of change. In the past, data engineers focused on building tools that make data-driven decisions possible. Now, data engineers are expected to provide the vision and leadership needed to drive their organizations towards a more data-driven future.
Choose The Right Programming Language To Learn
An engineer will need to be proficient with general programming skills and solve problems quickly and efficiently. Nevertheless, the primary language you will need to specialize in is Structured Query Language (SQL). This forms the backbone of creating databases that organize large amounts of data. Other important languages you should become proficient in include:
– Python: The most popular programming language that is used in enormous amounts of applications.
– Java: The second most popular language behind Python, it is used for many back-end development projects.
– R: Used for statistical computing.
Become Proficient With Automation And Scripting
This step is more beneficial for your own sanity. Many tasks you will be involved in are repetitive, and if you understand how to create simple or complex automation scripts, you will become far more efficient. The more efficient you are, the more desirable a candidate you will be when searching for a job.
Develop A Deep Understanding Of Databases
A database is a collection of data organized in a structured way to make it easier to retrieve, use, and update information. A database consists of one or more database tables that contain the actual data. As a data engineer, it will be your job to use your experience and problem-solving skills to set up systems that allow companies to retrieve and serve up information, among other things, rapidly. Therefore you must have a deep understanding of what they are, how they work, and what current bottlenecks endure in current designs.
Get to Know Data Processing
In data processing, raw data is transformed into applications that humans can use to perform different calculations. It would help if you got up to date with the tools used for various aspects, such as Apache Spark for parallel processing tasks.
Learn About Cloud Computing
Cloud computing is a rather complicated topic that requires a lot of knowledge. However, it is becoming more essential to at least get some understanding of how they work. More companies opt to store their vast quantities of data in the cloud rather than using an in-house server. This has several benefits for the company, such as saving money on maintenance and upkeep, but it gives you more work as a data engineer. In any case, it is always good to learn new things, and this could be the thing that makes you stand out among other candidates.
Have a Portfolio Ready
With any industry, you will need to prove you are capable of delivering what you say you will. This is especially true for data engineering jobs because you will compete with many other potential employees. Therefore you will need something that will help you to stand out and get you noticed. If you are brand new and don't have any experience, you can set up and maintain your own projects. If you have permission, you could set up a payroll management system for your university, or you could find some open-source data, like the movement of polar ice, and design a project to monitor it over time. Whatever you decide, it should ensure that your abilities get noticed.
Data science is full of options for you to pursue, from a job in business intelligence to working at a fintech company. All of these are viable, and you should take your time deciding which is the most enjoyable for you. You can also take many different paths to your position in the data science industry, and this guide will show you how to become a data engineer from the ground up by first getting a solid understanding of how data science is being done today.