The scope of the responsibilities of Data Engineers changed dramatically with the advent of “Big Data.” Technological developments helped evolve data science from dataset cleaning and statistical methods to a field that included data analysis, predictive analysis, data mining, business intelligence, machine learning, deep learning, and many more.
The data engineer is typically responsible for the management to ensure data workflows, pipelines, and ETL processes. It’s a combination of sorts between both the data analytics and the data scientist. With these essential functions in mind, today, it is the next hottest world that is gaining active momentum.
Are you interested in grabbing Big Data career opportunities? Think no more. Data engineers have a lucrative career path and will leverage further data science pipeline.
What Exactly is Data Engineering?
Data engineers are software engineering experts developing new methods to store and transfer large quantities of data. They design, build, and test data architectures and tools that enable easier access and interpretation of data in a business context.
Why Data Engineer?
Data Engineers use the work of the data architects as a step in the processing of the data available. These days, the demand for Big Data professionals is up by 50%. Forbes also said LinkedIn’s top new job ventures include machine learning engineers, data scientists, and large data engines.
Many people are creating high-remuneration career paths with big data. It often involves a bigger team to work with big data. They work with people in roles, namely Data Warehouse Engineers, Data Platform Engineers, Data Infrastructure Engineers, Analytics Engineer, Data Architects, and DevOps Engineers. Besides that, it is essential to employ data engineers at the top of any data-driven organization.
What does a Data Engineer do?
The Jedi Knights of data science are Data Engineers. They rely on a combination of analysis, knowledge, expertise, and judgment to make critical decisions for a company’s success. A data engineer is a self-starter influenced to bring out more tasks than usual. To capture, organize, analyze, and imagine massive data sets, Data Engineers implement complex, large-scale Big Data projects. They transform raw data into perspectives that come from different tools, techniques, and cloud-based platforms.
Data engineers take care of the construction and maintenance of ETL pipelines that make critical data available to the whole organization. They’re great team players. A data engineer understands when to actively collaborate to build solutions and platforms that satisfy or even exceed meeting the business needs of a company with data scientists and executives.
How to Become a Data Engineer?
This career path could be yours’ best choice if you are excited about Big Data career opportunities. The gateway to the job of a data engineer can be a development or software-engineering experience. But what if you’re new in the field and you don’t know how to get there? Then check this education and skills, which opens the door to a career in data engineering.
What Skills do needed to become a Data Engineer?
Consequently, if this job inspires you and you are enthusiastic, you can research, master all the skills you need, and become a master in data engineering. First of all, the primary focus of data engineering is on computer science. In specific, you need to understand practical algorithms and data structures. Secondly, since data engineers access the data, knowledge of database operations and the underlying structures is necessary. Check below for more skills to gain.
- Linux and the command line
- Programming Experience in Python or Scala/Java
- Knowledge of SQL
- Some awareness and distinction of distributed networks from conventional processing and storage frameworks
- Keen ecosystem awareness, including chugs (such as Kafka, Kinesis), processing frameworks (like Spark, Flink), and storage engines (such as S3, HDFS, HBase, Kudu)
- Know how reliable and fragile each tool is and how to accomplish usually
- Awareness of ways to access and process data
- Advanced analytics and programming skills
What Typical Education Background needed to become a Data Engineer?
Complete a bachelor’s degree in computer science and is usually a full-time course for three years.
Then, complete post-graduation in Master of Computer Science, a full-time course for two years.
It could be beneficial to advance your Data Engineering specialization through a Data Science Bootcamp or complete Data Engineering certifications recognized by the industry.
How Much a Data Engineer Earn?
Talking about the Data Engineer’s salary, it is one of the highest paid jobs across the globe. The salary differs from organization to organization, and the experience you hold. But as you gain more experience and bring value to the table, eventually your salary increases.
Upskill with an Online Short Course
Join online training immediately for these on-demand Data Engineer skills. To improve your career, ambitious Data Engineers can go on a certification course as this profession needs excellent technological knowledge. Few certifications for Data Engineers to consider are Cloudera Certified Professional (CCP) Data Engineer, Google Cloud Certified Professional Data Engineer, CPEE – Big Data Analytics and Optimization), and IBM Certified Data Engineer – Big Data. Join Data Engineering course training programs to gain a high-paying career in this field.
Explore your career to become Data Engineer
The processing and analysis of data have also been challenging, taking a great deal of expertise to acquire knowledge that can help the company take successful and informed actions that will lead to success. Many organizations need Data-engineers and other positions requiring grappling with large datasets.
Data Engineer path is one of the better choices you can have if you choose to excel in data science. Many companies prefer candidates with some professional software engineering expertise. Yet these days, companies are rising so quickly and are ready to take fresh CS/Bootcamp students.
According to one of the research studies, the Data Engineer job continues to be the top-of-the-line work with 88.3% growth in postings over the last 12 months. Look at these advanced career paths – Junior data engineer, Data engineer, Senior data engineer, Lead data engineer, Head of data engineering, and Chief data officer.
If you have no experience in software engineering or analytics but want to hold a position in data engineering, work on one or more projects that demonstrate what you can do. A data engineer can achieve an entry-level role that drives to a lucrative profession by showcasing specific skills and qualifications. Many people are willing to remain as a data engineer at the top level until retirement. Others might consider this milestone as an opportunity to gain another career.
