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The role of Azure Data Engineer is in high demand in the field of data management and analytics. As an Azure Data Engineer, you will be in charge of designing, building, deploying, and maintaining data-driven solutions that meet your organization’s business needs. This position requires knowledge of Microsoft Azure services such as Azure Data Factory, Azure Stream Analytics, Azure Databricks, Azure Cosmos DB, and Azure Storage. In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices
Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required. Experience with data warehousing and ETL concepts, as well as programming languages such as Python, SQL, and Java, is required. An Azure Data Engineer with these skills can effectively design, implement, and manage complex data-driven solutions that can drive business success.
Data is an organization’s most valuable asset, so making sure it can be accessed quickly and securely should be a top priority. This is where the Azure Data Engineer comes into play.
An Azure Data Engineer is a highly qualified expert who is in charge of integrating, transforming, and merging data from various structured and unstructured sources into a structure that can be used to build analytics solutions.
The Microsoft Certified Data Engineer is in charge of designing the entire architecture of the data flow while keeping the company’s business requirements in mind. Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs to provide end users with a variety of ready-made models. Azure Data Engineers use the Azure Form Recognizer service to automatically extract data from various documents and generate outputs. Data engineers are in charge of automating metric calculations with Azure Metrics Advisor and creating conversational chatbots with Azure Bot Service. There are numerous other Azure services that can assist Azure Data Engineers in expanding their capabilities. Let’s take a look at the factors that are driving the industry’s demand for Azure data engineers.
Why Do Companies Hire Azure Data Engineers?
The use of data has increased dramatically in recent years. Every day, more people, organizations, corporations, and other entities use data. Previously, people were more focused on meaningful insights and analysis, but they realised that data management is just as important. As a result, the role of data engineer in the technology industry has grown in importance. Data engineering is a new and evolving field that will withstand the test of time and computing advances. Certified Azure Data Engineers are frequently hired by businesses to convert unstructured data into useful, structured data that data analysts and data scientists can use. Data infrastructure, data warehousing, data mining, data modelling, and other tasks are all part of a company’s data science programme, and data engineers are in charge of the majority of them.
Microsoft Azure is a modern cloud platform that provides a wide range of services to businesses. It offers a number of certifications for mastering specific Azure skills. Every year, nearly 365,000 businesses register for Microsoft’s Azure platform, according to Microsoft. This demonstrates the high demand for Microsoft Azure Data Engineers. Every year, Azure’s usage graph grows, bringing it closer to AWS. Many enterprises, including Fortune 500 companies, trust and use Microsoft Azure. These businesses are transferring their data and servers from on-premises to the Azure Cloud. As a result, businesses require Azure Data Engineers to monitor big data and other operations at all times.
Azure Data Engineers Jobs – The Demand
According to Gartner, by 2023, 80-90 % of all databases will be deployed or transferred to a cloud platform, with only 5% ever evaluated for repatriation to on-premises. As long as there is data to process, data engineers will be in high demand. Data engineering was the top trending career in the technology industry in 2019, according to Dice Insights, beating out computer scientists, web designers, and database architects. According to the 2020 U.S. Emerging Jobs Report, data engineer roles are growing at a 35 percent annual rate.
This significant growth is frequently due to the fact that any organization intending to use data mining techniques and gain meaningful insights requires a secure data infrastructure. Keeping up with data management technologies can give data engineers a competitive advantage as the industry grows and evolves.
With the growing demand for data engineers, qualified data engineers’ salaries are likely to rise significantly.
Azure Data Engineer Skills
With the growing number of Azure Data Engineer roles, it is critical to have a thorough understanding of the skill sets required to be successful. The basic skills are applicable to any data engineer, regardless of cloud platform. The following are some of the fundamental foundational skills required of data engineers:
A data engineer should be aware of changes in the data landscape. They should also consider how data systems have evolved and how they have benefited data professionals.
Investigate the differences between on-premises and cloud data solutions. Furthermore, a thorough understanding of cloud technology’s business applications is advantageous.
A Data Engineer must be well-versed in the relevant industry and the responsibilities that come with it. It is also necessary to have a thorough understanding of Azure services.
To get a job as an Azure data engineer, you must also specialise in role-specific skill sets. The role-specific skills highlight the critical competencies and knowledge required by a data engineer to do their job. Here are some role-specific skills to consider if you want to become an Azure data engineer:
Programming languages are used in the majority of data storage and processing systems. Data engineers must be well-versed in programming languages such as Python, Java, and Scala.
The most common data storage methods are relational and non-relational databases. Understanding the database and its structures requires knowledge of SQL.
Data is moved from databases and other systems into a single hub, such as a data warehouse, using ETL (extract, transform, and load) techniques. Learn about popular ETL tools such as Xplenty, Stitch, Alooma, and others.
To store various types of data, various methods are used. It is preferable to understand when to use a data lake versus a data warehouse to create data solutions for an organisation.
Companies collect massive amounts of data, making automation essential for dealing with such massive amounts of data. Data engineers should be able to use scripts to automate repetitive tasks.
While data scientists are primarily concerned with machine learning, having a basic understanding of the concepts may help them better understand the data scientist demands on their teams.
Data engineers don’t just work with traditional data; they’re frequently tasked with handling massive amounts of data. A data engineer should be familiar with popular Big Data tools and technologies such as Hadoop, MongoDB, and Kafka.
Because companies are increasingly replacing physical servers with cloud services, data engineers must understand cloud storage and cloud computing.
While some businesses have specialised data security teams, many still rely on their data engineers to handle and store data in a secure manner to avoid loss or theft.
Finally, stay up to date on recent trends, feature updates, availability releases, and other aspects of new and existing Azure data resources. Many of these are available in Azure Updates, and engineers can filter product categories to find data engineering-specific materials.
What does an Azure Data Engineer Do?
Designing and putting into place data management solutions on the Microsoft Azure platform is the responsibility of an Azure Data Engineer. Data storage solutions, data pipelines, and data processing systems are all included in the designing, implementing, and maintaining of these. An Azure Data Engineer is primarily responsible for the following duties:
conceiving and implementing data storage solutions utilising Azure technologies like Azure Storage, Azure SQL Database, and Azure Cosmos DB
constructing data pipelines to transfer data to Azure data stores and process the data using Azure services like Azure Data Factory, Azure Stream Analytics, and Azure Databricks.
putting data processing solutions into practise using Azure services like Azure HDInsight, Azure Databricks, and Azure Machine Learning.
putting data security and privacy measures in place using Azure technologies like Azure Active Directory, Azure Key Vault, and Azure AD B2C.
Utilizing tools like Azure Monitor, Azure Log Analytics, and Azure Resource Manager, one can manage and monitor the performance and availability of Azure data solutions.
collaborating with other data team members, such as data scientists and analysts, to design and implement complete data solutions.
In summary, an Azure Data Engineer plays a critical role in designing, building, and maintaining the data management solutions on Microsoft Azure platform, ensuring that the data is secure, available, and processed efficiently to support business requirements.
So this was all about the Azure data engineer skills. This blog will be updated regularly to accommodate trends and current changes. If you have any other ideas or doubts about this topic, please leave a comment below.
Check out if you want to take the Azure data engineer certification course to get your CV shortlisted quickly.
If you are interested in learning further and want assistance with other certifications, you can visit our Edureka website. Until then, happy learning!
|DP 203: Data Engineering on Microsoft Azure|
Class Starts on 30th September,2023
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|DP 203: Data Engineering on Microsoft Azure|
Class Starts on 28th October,2023
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