Interested in becoming a Cloud Data Engineer on Microsoft Azure? Find out everything you need to know in this guide.
What is a Cloud Data Engineer?
A Cloud Data Engineer combines software engineering and data science skills to design scalable Big Data infrastructures. They transform and prepare data for its intended purpose.
For example, if data is needed for an automated recommendation engine, a cloud data engineer will build data pipelines that collect and transform data from various sources such as user account information, search terms, platform preferences, response to marketing messages, etc. Based on this, the recommendation engine automates real-time predictions for the user.
What are the missions of the Data Engineer in cloud computing?
He builds and supports data infrastructures that enable data-driven decision making. On the data layer, he collects, transforms and publishes data to be used for information. At the infrastructure level, he/she sets up data processing systems that allow data scientists to create machine learning models and make accurate predictions.
Some of the main responsibilities of a cloud engineer are:
- Design, build and operationalize data processing systems;
- Ensure the quality of data and solutions;
- Integrate distributed systems into a single source of truth;
- Design and maintain database systems;
- Transform various forms of data into a usable format;
- Operationalizing machine learning models.
In any organization, a data engineer plays a fundamental role in making data science, machine learning and artificial intelligence possible. They are the architects and engineers behind the pipelines through which data flows and reaches its destination, whether it is data science teams or enterprise applications.
To achieve this, they perform a series of tasks. Some of these are:
- Extracting data from various data source systems, transforming it into a staging area and loading it into a data warehouse system (also known as ETL).
- Architecture, creation and launch of data pipelines
- Using SQL, Cassandra, Bigtable… to analyze and report on data characteristics
- Monitoring systems on cloud infrastructures
- Automating processes for installation, configuration, monitoring, etc.
How to become a Microsoft Certified Data Engineer?
The Microsoft Azure Data Engineer certification is ranked as the “hardest to get” mainly due to the comprehensive nature of the concepts you will be tested for. It also goes beyond the standard multiple choice questions and includes various formats such as scenario-based questions that require you to think about the work you will be doing. It is for this reason that candidates are advised to undergo intensive training in Data Engineering on Azure.
Why is a Cloud Data Engineer certification an advantage for your resume?
Here are three reasons why you should get a cloud certification as a data engineer:
- Employers prefer certified Cloud Data Engineers and a Microsoft Azure certification is an added benefit.
- Certified Cloud Data Engineers are paid more and receive a pay raise after certification.
- A Cloud Data Engineering certification is a career booster, whether you are a specialist in a niche or a generalist project/team leader.
Translated from Formation Microsoft Azure : se former au Data Engineering sur le cloud de Microsoft
