An Azure data engineer uses Microsoft cloud services to collect, clean, organize, and present data to the business user. In other words, an Azure data engineer builds data processing pipelines and creates analytics solutions using Azure cloud tools.
For example, the Microsoft Azure data factory is used to build high-performing ETL pipelines that takes in data and processes it for errors and re-organization.
Azure data engineers would organize data into compact tables and comply with the data quality checks. Thus, a database is configured, maintained and deployed by Azure data engineers.
The more specific tasks of an Azure data engineer are as follows:
Job description– what does an Azure data engineer do?
An Azure data engineer uses Azure data services and frameworks to accomplish the following:
- Create Entity Relationship (ER) diagrams and design tables with perfect referential integrity and semantic accuracy
- Write relational database queries; demonstrate a remarkable ability to fetch data from multiple tables
- Perform data integration and ETL functions that effectively prepare data for presentation and reporting
- Update and maintain the existing data warehouse, data lake or big data storage system
- Ensure compliance of the stored data against the data quality dimensions
- Use visualization tools and build insightful dashboards that reflect business processes
- Migrate existing on-premise workloads (SSIS packages) to Azure Data Factory (ADF)
Skills of an Azure data engineer
- Hands-on proficiency in Azure Data Factory (ADU), Azure Devops, Azure Data Lake
- Experience with Microsoft SQL Server tools (SSIS, SSRS, and SSAS)
- Expertise in Microsoft Power BI and an eye for data visualization
- Proficiency in data processing languages; preferably T-SQL, Python and Scala
- Impressive problem solving ability
- Excellent communication skills
What is salary of an Azure Data Engineer?
An Azure data engineer makes an average salary of $123,000/yr that includes a basic pay of 102,000/yr.
A senior Azure data engineer– with an experience of 2-4 years, further increases the range with up to an additional $30,000/yr and can make an average of $150,000/yr.
For higher experienced individuals– between 5-7 years, at the lead position, the average salary is highest and estimates to $160,000/yr.
Is Azure Data Engineering hard to learn?
Data engineering might feel hard at the first glance. However, the concepts are extremely simple at the core. For example, ER diagrams might make you feel overwhelmed with the relations of data it contains, but once you understand the basic relations and why they connect with each other, it becomes extremely simple for you to create dense logical diagrams.
Therefore, it’s advised that you take some time with data engineering concepts. And once you grab a concept, you’re gonna be head and shoulders above others.
It’s also true that data engineering is high in demand because not a lot of people are willing to put effort in it. It only requires your determination and patience to be successful in the field. After that, you would witness that the jobs in the data engineering market offer incredible financial and professional benefits.
Is Azure Data Engineering a good career?
The cloud era continuously pushes data engineering on Azure. The market share of Azure Data Factory for example is reportedly 6.34%. About 4 years ago, more than 11,000 companies were using Azure Data Factory as their prime data engineering platform. These factors demonstrate the demand for Azure data engineering skills.
The Microsoft official certification– Azure data engineering associate, further demonstrates the demand in the career. The certification exam evaluates skills in Azure tools for data engineering such as Azure Data Factory, Azure Data Lake, Azure Stream Analytics etc.
To wrap up the whole discussion, Azure data engineer performs the prime role that uses Microsoft cloud technology to provide the essential wisdom for running business operations.
