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Over the years, the 'data' field has undergone a paradigm shift. Earlier, focus revolved around the retrieval of useful insights, but recently, data management has gained recognition. As a result, the role of data engineers has slowly come into the spotlight.
Data engineers extract and acquire data from different sources, including the database – it can be SQL Server, Oracle DB, MySQL, Excel, or any other data storing or processing software. Afterward, they apply algorithms on this data and make it useful so it can assist different departments like marketing, sales, finance, and others to introduce more productivity in their work. For instance, data engineers can help an e-commerce business learn which of their products will have more demand in the future. Similarly, it can allow them to target different buyer personas and deliver more personalized experiences to their customers.
In the past few years, the demand for data engineer jobs has risen astronomically. Organizations are actively looking for data engineers to address their data woes. Data engineers should have knowledge about database systems and data warehousing. Data engineers should also know how to perform a comparative analysis of data stores. Data engineers should also understand relational database designs, and have proficiency in both SQL and NoSQL domains. Here are certain essential Data Engineer skills:
1. SQL and NoSQL
SQL and NoSQL are must-haves for any data engineer. SQL is the primary programming language for managing and creating relational database systems. Relational database systems are tables that contain rows and columns and are widely popular. On the other hand, NoSQL databases are non-tabular and are of various kinds according to the data model. Common examples of NoSQL databases are documents and graphs.
You should know how to work with Database Management Systems (DBMS) and for that, you’d need to be familiar with SQL and NoSQL. Some additional SQL skills include MongoDB, Cassandra, Big Query, and Hive. By learning about SQL and NoSQL, you can work with all kinds of database systems.
2. Data Warehousing
Data warehouses enable you to store large amounts of data for query and analysis. The data can come from multiple sources such as ERP software, accounting software, or a CRM solution. Organizations use this data to generate reports, perform analytics, and data mining to generate valuable insights.
You must be familiar with the basic concept of data warehousing and the tools related to this field, Amazon Web Services, and Microsoft Azure. Data warehousing is among the fundamental skills required for data engineering professionals.
3. ETL Tools
ETL stands for Extract, Transfer, Load, and denotes how you extract data from a source, transform it into a format, and store it into a data warehouse. ETL uses batch processing to ensure users can analyze relevant data according to their specific business problems.
It gets data from multiple sources, applies particular rules to the same, and then loads the data into a database where anyone in the organization can use or view it. As you may have realized, ETL tools are among the most important skills for data engineering professionals.
4. Programming Skills
Python and Java are some of the most popular programming languages. Python is a must have for a data engineer as it helps you perform statistical analysis and modelling. On the other hand, Java helps you work with data architecture frameworks.
You should note that nearly 70% of job descriptions for data engineer jobs require Python as a skill. As a data engineer, you must have strong coding skills as you’d need to work with multiple programming languages. Apart from Python, other popular programming skills include .NET, R, Shell Scripting, and Perl.
Another language to watch out for is C++. It can compute vast amounts of data in the absence of a predefined algorithm. Moreover, it’s the only programming language that lets you process more than one GB of data within a second. Apart from these advantages, C++ also lets you apply predictive analytics in real-time and retrain the algorithm. It’s among the most important skills required for data engineers.
5. Apache Hadoop
Apache Hadoop is an open-source framework that lets you store and manage Big Data applications. These applications run within cluster systems and Hadoop helps you manage the same. One of the most important data engineering skills is to create Hadoop applications and manage the same effectively. Since its arrival in 2006, Hadoop has become one of the must haves for any data professional. It has a wide collection of tools that make data implementations easier and effective.
Hadoop lets you perform distributed processing of large datasets by using simple programming implementations. You can use R, Python, Java, and Scala with this tool. This framework makes it affordable for companies to store and process large amounts of data as it lets them perform the tasks through a distributed network. Apache Hadoop is an industry staple and you should be well-acquainted with it.
6. Machine Learning
Machine learning has become one of the most popular technologies in the last few years. A machine learning algorithm helps you predict future results by using historical and present data.
As a data engineer, you only need to be familiar with the basics of machine learning and its algorithms. Being familiar with machine learning will help you in understanding your organization’s requirements and collaborate with the data scientist more efficiently. Apart from these benefits, learning about machine learning will help you in building better data pipelines and produce better models.
Future of Data Engineer Jobs
Data engineer jobs are in high demand. The Bureau of Labor Statistics (BLS) places the job title data engineer in the categories of statisticians and computer and information research scientists. For a statistician, the projected job growth between 2020 to 2030 is 33 percent, and for a computer and information research scientist, the projected job growth between 2020 to 2030 is 22 percent. According to the BLS projections, the job of a data engineer is likely to increase in demand significantly in the next four to five years, making this career a good career path to pursue.
