Azure Data Engineer Skills

Skills Required for Azure Data Engineer

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A wave of colorful code or data streams out of the laptop screen and flows around the person

Primary Skills

The skills listed below are essential for becoming a proficient Azure Data Engineer and excelling in the role

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Azure Data Services

It's a collection of data management and analytics tools provided by Microsoft Azure that are based on the cloud. It includes services related to data. Engineers use it to handle and analyze data for better decision making.

Data Integration

The process involves making data from various sources usable and meaningful, for analysis and reporting purposes. It allows Azure data engineers to easily connect, transform and transfer data, within the ecosystem

Data Modeling

It is the method of creating a visual representation of data structure, relationships, and entities within a software system. Data engineers utilize it to convert data solutions into a well-structured, aligned, and performant business goal.

SQL and T-SQL

It is a query language Azure data engineers use for data manipulation, querying, and managing databases.

Big Data Technologies

It is a set of software tools, frameworks, and technologies that Azure data engineers utilize to handle and process large and complex datasets.

Data Warehousing

It is a part of a data management system intended to facilitate BI activities and analytics.

Data Visualization

The process involves representing data using graphics, charts and animations. Engineers use this method to ensure that data is effectively prepared, stored and easily accessible for analysts.

Azure Machine Learning

It is a cloud-based service issued by Microsoft Azure that allows data engineers to easily build, deploy, and manage complex models.

Data Security and Compliance

Data security and compliance encompass aspects that involve identifying regulations for safeguarding data. Furthermore, it assists Azure data engineers in implementing measures, within Azure based solutions to ensure the protection of data complied with regulations and prevent any data breaches.

Azure Cognitive Services

It is a set of Azure APIs that helps Azure bring AI within the reach of data engineers. Using this, they enhance apps, evaluate user experience, and process natural language.

Data Quality and Governance

Data engineers employ data quality to assess the precision and comprehensiveness of data while governance is employed to establish protocols that guarantee data quality, security and adherence to regulations.

Data Pipelines and Orchestration

Using this robust tool, Azure data engineers can automate workflows, schedule jobs, and coordinate dependencies.

NoSQL Databases

It is a native non-relational service that enables Azure data engineers to work on document data models. Furthermore, Azure Cosmos DB, a widely used NoSQL database service, allows them to store JSON documents with customizable schema.

Data Streaming

Data streaming is a method that assists Azure data engineers in examining data in time. It operates on cloud platforms. Can also be utilized for implementing scalable analytics solutions.

Azure Data Catalog

It is a metadata catalog that assists Azure data engineers in data asset discovery. It lets them register, discover, and analyze data sources.

Azure Data Services: It's a collection of data management and analytics tools provided by Microsoft Azure that are based on the cloud. It includes services related to data. Engineers use it to handle and analyze data for better decision making.
Data Integration: The process involves making data from various sources usable and meaningful, for analysis and reporting purposes. It allows Azure data engineers to easily connect, transform and transfer data, within the ecosystem.
Data Modeling: It is the method of creating a visual representation of data structure, relationships, and entities within a software system. Data engineers utilize it to convert data solutions into a well-structured, aligned, and performant business goal.
SQL and T-SQL: It is a query language Azure data engineers use for data manipulation, querying, and managing databases.
Big Data Technologies: It is a set of software tools, frameworks, and technologies that Azure data engineers utilize to handle and process large and complex datasets.
Data Warehousing: It is a part of a data management system intended to facilitate BI activities and analytics.
Data Visualization: The process involves representing data using graphics, charts and animations. Engineers use this method to ensure that data is effectively prepared, stored and easily accessible for analysts.
Azure Machine Learning: It is a cloud-based service issued by Microsoft Azure that allows data engineers to easily build, deploy, and manage complex models.
Data Security and Compliance: Data security and compliance encompass aspects that involve identifying regulations for safeguarding data. Furthermore, it assists Azure data engineers in implementing measures, within Azure based solutions to ensure the protection of data complied with regulations and prevent any data breaches.
Azure Cognitive Services: It is a set of Azure APIs that helps Azure bring AI within the reach of data engineers. Using this, they enhance apps, evaluate user experience, and process natural language.
Data Quality and Governance: Data engineers employ data quality to assess the precision and comprehensiveness of data while governance is employed to establish protocols that guarantee data quality, security and adherence to regulations.
Data Pipelines and Orchestration: Using this robust tool, Azure data engineers can automate workflows, schedule jobs, and coordinate dependencies.
NoSQL Databases: It is a native non-relational service that enables Azure data engineers to work on document data models. Furthermore, Azure Cosmos DB, a widely used NoSQL database service, allows them to store JSON documents with customizable schema.
Data Streaming: Data streaming is a method that assists Azure data engineers in examining data in time. It operates on cloud platforms. Can also be utilized for implementing scalable analytics solutions.
Azure Data Catalog: It is a metadata catalog that assists Azure data engineers in data asset discovery. It lets them register, discover, and analyze data sources.

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Secondary Skills

Data Compression and Encryption
Data compression aims to reduce the size of data while data encryption is used to ensure the security of information.
Python or R Programming
These two programming languages are in the Azure ecosystem. They allow Azure data engineers to build applications from scratch.
Azure Data Explorer (ADX)
It is a reliable and fast data analytics service that allows Azure data engineers to analyze large sets of data with ease.
Data Backup and Recovery
This fully managed backup service allows engineers to centralize and automate backup in Azure.
Azure Logic Apps
This cloud service focuses on workflow automation and integration. Azure engineers must understand this cloud service well as it helps them integrate various services within Azure.
Azure Data Migration
This tool allows Azure data engineers to automate data migration to Azure.
Data Partitioning and Sharding
This type of horizontal partitioning helps Azure data engineers divide large databases into small databases. It even comprises breaking data into smaller segments or shards, each managed independently.
Azure Data Share
It is a safe and secure service that enables Azure data engineers to share data with customers and teammates.
Azure Data Bricks
Azure Databricks is an analytics platform that leverages Apache Spark to handle volumes of data. Additionally, it offers an environment where you can securely store, process and analyze data on a scale.
Azure Data Factory Mapping Data Flows
These are visually designed data transformations that allow Azure data engineers to develop data transformation logic.
Azure Data Lake Analytics
It is an on-demand analytics service that helps Azure data engineers simplify big data sets.

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Associated Soft Skills

Communication Skills

Effective communication makes the transition of information seamless and ensures that no information is being misinterpreted. This skill is necessary for Azure data engineers as it will help them collaborate smoothly with cross-function teams.

Problem-Solving

This skill is essential for Azure data engineers to address technical issues confidently and easily. It even helps them resolve data-related problems to maintain quality.

Adaptability

Azure developers are required to work with ever-changing technologies and tools. Thus, having an adaptable nature embraces them to accept change and bring innovation.

Time Management

Time management ability promotes Azure data engineers to effectively manage and meet deadlines on time.

Continuous learning

Staying updated with the latest tools and techniques fosters professional growth and helps Azure data engineers remain competitive in their roles.

Teamwork

Teamwork is essential for Azure Data Engineers as it contributes to collaborative efforts and the success of the project.

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Other Related Skills

Azure Devops Engineer Skills

Azure Administrator Skills

Cloud Developer Skills

Frequently Asked Questions

What are the key responsibilities of an Azure Data Engineer?

Azure Administrators have the responsibility of creating, executing and overseeing data solutions on Azure. Furthermore, they are also expected to have a strong understanding of data integration, storage, processing, and analysis.

What are the key responsibilities of an Azure Data Engineer?

The key responsibilities of an Azure Data Engineer is to handle tasks such as creating data models integrating data transforming data and ensuring the security and compliance of data. They are also responsible for optimizing data pipelines and ensuring the performance of data solutions.

How can a Skill Intelligence Platform help build a top-performing Azure Data Engineer team?

Skill Intelligence platforms like iMocha can help you make intelligent talent decisions and work towards building future-ready skill-fit team. Using this tool, you can easily define the skills of Azure Data Engineer in a defined architecture and validate them to deploy them to the right role.