Azure Data Platform Roles
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Azure Data Platform Roles

Updated: Oct 20, 2021

Do you have a clear understanding of the difference between a Data Engineer and a Data Administrator? How is Azure AI Engineer different from Data Scientist?



If there is any doubt, here are the main differences and responsibilities.


There is a total of 5 roles and 5 role-based certifications offered by Microsoft for the people who deal with cloud-focused data.


  • Azure Database Administrator

  • Azure Data Engineer

  • Azure Data Analyst

  • Azure Data Scientist

  • Azure Artificial Intelligence Engineer


Azure Database Administrator

Role Description: As the title implies, it's an administrator. He is responsible for building and managing cloud-based solutions, aka databases, and hybrid solutions (involving SQL Server databases located in the different public or private cloud services and on-premises).


Tools and services used: Azure ARM Templates, Azure CLI, Powershell, Management Studio, Azure SQL Database, Azure Synapse Analytics. Azure database administrator also uses Transact SQL but only for administrative management purposes.


Azure Data Engineer

Role Description: Designing and implementation the management, monitoring, security and privacy aspects of data.


Tools and services used: Data Engineer is using a full stack of Azure data services to satisfy business needs. Azure SQL Database, Azure Data Factory, Azure Logic Apps, Azure Kusto service, Azure Databricks, Azure HDInsights, Azure Synapse Analytics.


Azure Data Analyst

Role Description: enables businesses to maximize the value of their data assets and is also responsible for designing and building data models inside Power BI, including data cleaning and transformations.


Tools and services used: Uses Power BI to build meaningful data visualizations.


Azure Data Scientist

Role Description: Someone who can predict the future using the data patterns from the past. Applies their knowledge of data science and machine learning to implement and run machine learning workloads in Azure.


Tools and services used: Azure Machine Learning Service, Data Science Virtual machines, HDInsight Spark and Hive Clusters, Azure Synapse Analytics, Azure Data Lake, Azure Databricks.


Azure Artificial Intelligence Engineer

Role Description: A software engineer who designs and develops intelligent solutions that encapsulate artificial intelligence.


Tools and services used: Azure Cognitive Services, Azure Machine Learning, Azure Bot Service, Azure Cognitive Search and knowledge mining, natural language processing etc.

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