Data engineering and data science have been one of the hottest trends in the vocational market for quite some time. Given the prediction by industry pundits and researchers, the demand for these two roles will witness a massive surge in the coming time. To build a successful career in data engineering, the aspirants need to understand data engineering skills completely.
Source: Springboard
Covering basics first, data engineers are information technology professionals with expertise in diverse applications and processes. Data engineering and data science are the two branches working in conjunction with each other and can extract the best of raw and unstructured data. Data engineers act as a rope bridge for data scientists as they efficiently build pipelines that transform raw data into consumable data formats. Data engineers also play a crucial role in optimizing the data recovery process, developing dashboards, and generating reports.
In this article, we will explore what data engineers do, the essential skills required to be a data engineer, and how to start a career in data engineering.
Multiple data science projects deploy various architectures, and data engineers are responsible for developing and maintaining the such architecture. They ensure that data flow between servers and applications remains uninterrupted. The data engineering branch combines the best of data science and software engineering elements.
The primary functions of a data engineer include:
Data engineers must possess the following technical and professional skills to build a successful career in data engineering. These are some of the most in-demand data engineer skills sought by prospective employers while hiring. Let’s look at them:
Database Systems
While speaking of technical skills required to be a data engineer, SQL and NoSQL are among the most sought-after. To be a successful data engineer, you should know how to efficiently work on and manipulate diverse database management systems for storing and retrieving information.
Data Warehousing Solutions
It is a simple job for data engineers to work on massive piles of data. While this data is extracted and lifted from multiple and extensive sources, data engineers must be well-versed with varied data warehousing solutions like MarkLogic, Oracle, Amazon RedShift, and so on.
ETL Tools
ETL Tools, also known as Extract, transfer, and load tools, belong to a technology category. They are responsible for gathering, moving, and reading raw data from multiple sources into a database or a BI (business intelligence) platform. The whole process aims to collect and analyze the right data to solve a specific business problem. This is one of the must-have data engineer skills.
Machine Learning Algorithms
Machine Learning or ML Algorithms is a specific science that makes future predictions based on previous data sets. Since it is the primary job of data engineers to collaborate closely with data scientists, it is an imperative data engineer skill to have a basic understanding of ML algorithms.
Source: Udacity
Programming Languages
A data engineer must have a fair to a deep understanding of the common programming languages. All employers want to hire data engineers to have an understanding of the following programming languages for statistical analysis and modeling:
Amazon Web Services (AWS)
Data engineers constantly harness AWS for designing automated data flows while ensuring its dexterity, innovation, and scalability.
Big Data
Big data stands for large chunks of structured and unstructured data. Big data forms a vital tool for data scientists and AI experts and makes it necessary for data engineers to have an exhaustive understanding of working with big data. This includes the processes starting from learning to store, clean, process, and extract information from the data.
Automation & Scripting
Since it is a simple job for data scientists to deal with large chunks of data, it becomes crucial for them to possess scriptwriting skills to automate repetitive tasks and save time and effort.
Apart from the technical skills discussed above, it is highly crucial and advantageous for data engineers to possess the following business skills. Combining these two skill sets is the key to a successful run in data engineering. Let’s have a look at some of these business skills:
Analytical Problem Solving Skills
A data engineer’s job involves addressing high-level challenges on an everyday basis. They must keep a clear eye on the important ones while deploying the right approach and methods to make the most of given time and resources.
Impeccable Communication Skills
As a data engineer, you may be faced with situations where you’ve to explain the core technical aspects to completely non-technical persons. To thrive in such situations effectively, it is crucial to possess effective communication skills. Data engineer has to share their findings and suggestions with peers from data science and architects regularly with the help of clear and astound communication skills.
Intellectual Inquisitiveness
Possessing intellectual curiosity and a certain level of inquisitiveness is a must-have data engineering skill. This helps data engineers explore new avenues and territories to get out of the league and find creative and unusual ways to solve complex data issues.
Deep Industry Knowledge
To be a successful data engineer, it is highly crucial to have an in-depth understanding of how your chosen industry functions. This helps immensely in making data engineers understand how data is collected, analyzed, and used.
If you aspire to become a data engineer, follow the simple steps explained below:
Data engineering career continues to grow steadily and offers lucrative job opportunities in diverse industries and sectors. The above article is a brief guide to the road map of becoming a successful data engineer by understanding the must-have data engineering skills.
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