The evolution of big data and its massive rise in relevance amongst industries across the world has created a need for data engineers who can proficiently collect and manage large quantities of data. With data becoming a major currency of the present age, data engineering has subsequently become one of the lucrative career options of the 21st century. This article takes a close look at who is a data engineer and what are the required data engineering skills.
What is the Role of a Data Engineer?
Data engineering at its core is the art of designing and developing advanced systems for collecting, storing, and analyzing data at a large scale. Data engineers are tasked with the responsibility of designing pipelines and pathways that transport data while transforming it into a usable form for data scientists and analysts. Data engineers should also be able to
- Build data warehouses to efficiently store data and make it capable of easy retrieval
- Analyzing the data, ensuring it complies with data governance rules and regulations.
- Understanding the pros and cons of data storage and query options.
Data engineers need to collect data from various sources, and then store these huge trenches of data under a single database that can represent this data as a uniform source of information. The ultimate goal of a data engineer is to make data accessible so that organizations can use it to evaluate and optimize their performance. A data engineer who’s well endowed with all the necessary data engineering skills can support the organization from the inside out and lead to an overall rise in performance and efficiency.
Data Engineering Skills
There are certain basic skills that you’ll need to master if you want to become a remarkable data engineer. Here are a few skills you’ll need.
Being proficient in coding languages is one of the most important data engineering skills that you should master. Taking courses and completing assignments are some of the most common ways to improve your coding skills. Some of the most common programming languages that data engineers use are SQL, NoSQL, Python, Java, R, and Scala.
Data warehousing is very important when it comes to managing huge amounts of data coming in from diverse sources wherein you need to apply ETL (Extract Transform Load). Informatica & Talend are the two well-known tools used in the industry. Data warehousing is also a very crucial tool for data analysts, and should big data engineers master warehousing, it becomes easier for them to learn new tools based on the already mastered fundamentals.
Hadoop Based Technologies
The arrival of big data and its rise in use led to the development of a whole new framework, Hadoop. Hadoop is a framework that not only stores Big Data in a distributed manner but also processes the data parallelly. There are certain tools in the Hadoop framework that are a part of fundamental data engineering skills. Some of these tools that you’ll need to master are HDFS, Yarn, PIG & HIVE, ZooKeeper, etc.
A major source of data is a database and thus it only makes sense that a data engineer should have adequate knowledge when it comes to database design & database architecture like 1-tier, 2-tier, 3-tier, and n-tier. Data models and Data schema are also key data engineering skills that an aspiring data engineer should master.
Data engineering is a broad field of study that the world is increasingly depending upon. Data engineers have never been in higher demand, and data engineering aspirants are constantly looking for ways to learn and understand more and more data engineering skills. Praxis understands this need and trend and has developed India’s first Post Graduate Program in Data Engineering. Our 6-month long PGP in Data Engineering will train you in all the skills required to become an outstanding data engineer, and our astounding placement records just act as testimony to the fact that we could indeed be the ideal destination for your data engineering career.