How to Become an Azure Data Engineer in 2024?
Your go-to guide with resources to become an Azure Data Engineer from the ground up.
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Planning to land a successful job as an Azure Data Engineer? Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer.
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Start ProjectThe big data industry is flourishing, particularly in light of the pandemic's rapid digitalization. Companies in various sectors are improving their big data and analytics operations, from healthcare to retail. The Bureau of Labor Statistics (BLS) states that data-related professions will rise by 12% by 2028, resulting in 546,200 new jobs. In every case, data engineering is expected to be one of the most in-demand professions in 2022 and beyond.
Table of Contents
- Who is an Azure Data Engineer?
- Why Do Companies Hire Azure Data Engineers?
- Azure Data Engineers Jobs - The Demand
- Azure Data Engineer Salary
- Azure Data Engineer Skills
- What does an Azure Data Engineer Do?
- Azure Data Engineer Job Description | Accenture
- Azure Certified Data Engineer
- Azure Data Engineer Certification
- Microsoft Azure Projects for Practice to Enhance Your Portfolio
- FAQs
Who is an Azure Data Engineer?
Data is an organization's most valuable asset, so ensuring it can be accessed quickly and securely should be a primary concern. This is where the Azure Data Engineer enters the picture.
An Azure Data Engineer is a highly qualified expert responsible for integrating, transforming, and merging data from various structured and unstructured sources into a structure used to construct analytics solutions.
The Microsoft Certified Data Engineer is in charge of creating the data flow's complete architecture while also considering the company's business requirements. Azure Data engineers work with Azure AI services developed on top of Azure Cognitive Services APIs to supply end-users with various types of ready-made models. Azure Data Engineers use the Azure Form Recognizer service to extract data from various documents and generate outputs automatically. The data engineers are responsible for automating metric calculations using the Azure Metrics Advisor and developing conversational chatbots using the Azure Bot Service. There are plenty of other Azure services that help Azure Data Engineers expand their capabilities. Let's look at the factors fueling the industry's demand for Azure data engineers.
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Why Do Companies Hire Azure Data Engineers?
The use of data has risen significantly in recent years. More people, organizations, corporations, and other entities use data daily. Earlier, people focused more on meaningful insights and analysis but realized that data management is just as important. As a result, the role of data engineer has become increasingly important in the technology industry. Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use. Data infrastructure, data warehousing, data mining, data modeling, etc., are part of a company's data science program, and data engineers handle most of these tasks.
Microsoft Azure is a modern cloud platform that offers businesses a wide range of services. It provides several certifications for mastering specific Azure skills. According to Microsoft, almost 365,000 businesses register for the Azure platform each year. This indicates that Microsoft Azure Data Engineers are in high demand. Azure's usage graph grows every year, bringing it closer to AWS. Microsoft Azure is trusted and adopted by many enterprises, including Fortune 500 companies. These companies are migrating their data and servers from on-premises to Azure Cloud. As a result, businesses always need Azure Data Engineers to monitor big data and other operations.
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View All ProjectsAzure Data Engineers Jobs - The Demand
"By 2022, 75% of all databases will be deployed or transferred to a cloud platform, with only 5% ever evaluated for repatriation to on-premises," according to Gartner. Data engineers will be in high demand as long as there is data to process. According to Dice Insights, data engineering was the top trending career in the technology industry in 2019, beating out computer scientists, web designers, and database architects. According to the 2020 U.S. Emerging Jobs Report, data engineer roles continuously rise, with roughly 35 percent average yearly growth.
This significant growth is often because any organization intending to apply data mining techniques and gather meaningful insights needs a secure data infrastructure. Staying on top of data management technologies can help data engineers gain an advantage in the industry as it grows and develops.
With the growing need for data engineers, you will likely see a significant boost in salary for qualified data engineers.
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Azure Data Engineer Salary
The average azure data engineer pay is $130,982 annually in the United States. The starting salary for entry-level positions is $117,000 annually, with most experienced individuals earning $160,000 annually.
In India, the national average compensation for an Azure Data Engineer is 7.01.085INR. The highest annual income for an Azure Data Engineer in India is 18,30,662INR, and the lowest yearly salary for an Azure Data Engineer in India is 4,00,000INR.
Azure Data Engineer Skills
With the increasing number of Azure Data Engineer roles, it is important to have an in-depth understanding of the skill sets to become successful. The fundamental skills apply to any data engineer, regardless of the cloud platform. The following are some of the essential foundational skills for data engineers-
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A data engineer should be aware of how the data landscape is changing. They should also be mindful of how data systems have evolved and benefited data professionals.
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Explore the distinctions between on-premises and cloud data solutions. Furthermore, a thorough understanding of the business applications of cloud technologies is advantageous.
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A Data Engineer must have a thorough understanding of the relevant industry and the responsibilities that come with it. Also, it’s essential to have an in-depth understanding of Azure services.
To secure an Azure data engineer job, one must also specialize in role-specific skillsets. The role-specific skills underline the critical competencies and knowledge that a data engineer requires to do their job. Here are some role-specific skills you should consider to become an Azure data engineer-
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Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala.
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Relational and non-relational databases are among the most common data storage methods. Learning SQL is essential to comprehend the database and its structures.
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ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Get familiar with popular ETL tools like Xplenty, Stitch, Alooma, etc.
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Different methods are used to store different types of data. It is better to know when to employ a data lake vs. a data warehouse to create data solutions for an organization.
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Companies collect large amounts of data, making automation vital for working with such big data. Data engineers should be able to automate repetitive operations using scripts.
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While data scientists are primarily concerned with machine learning, having a basic understanding of the ideas might help them better understand the demands of data scientists on their teams.
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Data engineers don't just work with conventional data; and they're often entrusted with handling large amounts of data. Hadoop, MongoDB, and Kafka are popular Big Data tools and technologies a data engineer needs to be familiar with.
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Companies are increasingly substituting physical servers with cloud services, so data engineers need to know about cloud storage and cloud computing.
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While some businesses have specialized data security teams, many still depend on their data engineers to safely handle and store data to prevent loss or theft.
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Finally, be familiar with recent trends, feature changes, availability releases, and other aspects of new and existing Azure data resources. Many of these can be found in Azure Updates, and engineers can filter the product categories to locate data engineering-specific materials.
What does an Azure Data Engineer Do?
This section lists all the roles and responsibilities one must perform as a Microsoft Azure Data Engineer.
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Data platform technologies on-premises and on the cloud are delivered and established by data engineers. Azure data engineers are responsible for securing and managing data flow from many structured and unstructured data systems. Some data systems are relational databases, nonrelational databases, data streams, and file stores. Data engineers are responsible for making data services work together safely and smoothly with other data platform technologies or services like Azure Cognitive Services, Azure Search, etc.
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They interact with business stakeholders to discover and address data requirements. They need to come up with ideas and put them into action. They are also responsible for managing, monitoring, and ensuring data security and privacy to meet corporate needs.
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Azure data engineering professionals are required to possess the potential to overcome business challenges by combining one or more Azure Data and Azure Synapse Analytics services with data pipelines, data streams, and system integration to solve business problems.
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Data engineers are responsible for using Power BI, Azure API Apps, or any modern visualization tool or platform to present data to end-users.
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Another core responsibility of an Azure Data Engineering professional is to analyze current company practices, processes, and procedures to develop new ways to use Microsoft Azure data and analytics PaaS services in the future.
To help you better understand the roles and responsibilities of an Azure Data Engineer, here's a quick overview of the Azure Data Engineer job description for Accenture-
Azure Data Engineer Job Description | Accenture
An Azure Data Engineer at Accenture is developing, deploying, and maintaining Microsoft BI solutions to fulfill market and customer needs. To help a customer, project, or entity, they must use knowledge of technologies, applications, techniques, procedures, and tools. They must be well-versed in the Microsoft BI Stack technical level (T-SQL, SSIS, SSAS, SSRS). Additional reporting skills are desirable, such as Oracle BI or Power BI. They will be responsible for designing and building software products on the Azure platform to implement new functionalities and support the current services as part of a collaborative team and under the supervision of a project manager.
Azure Certified Data Engineer
The Microsoft Azure Data Engineer Associate certification is crucial for becoming a successful Microsoft Certified Azure Data Engineer Associate. Previously, the certification path included two tests- DP-200 and DP-201, that tested the diverse competencies of Azure data engineers. The Data Engineering on Microsoft Azure DP 203 certification exam, which replaces the previous two tests, was launched in June 2021 by Microsoft.
What is the Microsoft Azure Data Engineer certification exam?
Microsoft Azure Data Engineers who take the Microsoft Azure Data Engineer Associate (DP-203) exam should combine data from different structured and unstructured data systems into structures used to construct analytics solutions. This test assesses the ability to plan and implement data storage, data processing, and security, and it also tests how well one can monitor and optimize data storage and processing.
Who should take the certification exam?
The Data Engineering on Microsoft Azure (DP-203) exam is for candidates who work as Data Engineers on Microsoft Azure. To become a Microsoft Certified Azure Data Engineer, you must thoroughly understand data computation languages like SQL, Python, or Scala and parallel processing and data architecture concepts.
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Skills Measured in the Exam
The following is a list of the topics covered in the DP-203 exam, along with their weightage-
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Design and Implement Data Storage (40-45%)
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Design a data storage structure
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Design a partitioning strategy
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Design the serving layer
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Implement physical data storage structures
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Implement logical data structures
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Implement the serving layer
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Design and Develop Data Processing (25-30%)
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Ingest and transform data
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Design and develop a batch processing solution
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Design and develop a stream processing solution
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Manage batches and pipelines
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Design and Implement Data Security (10-15%)
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Design security for data policies and standards
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Implement data security
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Monitor and Optimize Data Storage and Processing (10-15%)
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Monitor data storage and data processing
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Optimize data storage and data processing
Azure Data Engineer Certification
Here are a few useful Microsoft Azure Certifications one can explore to become a certified Azure data engineer.
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Microsoft Certified: Azure Data Fundamentals
The certification provides the technical skillset you will need to begin working with data in the cloud. By mastering the fundamentals, you can accelerate your career and get ready to explore more of Azure's technical opportunities.
This certification evaluates your ability to carry out the following tasks:
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define key data concepts;
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describe considerations for working with relational data on Azure;
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specify considerations for working with non-relational data on Azure;
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and define an analytics workload on Azure.
If you intend to take the exam, you should be familiar with the fundamentals of relational and non-relational data and various data workloads like analytical or transactional.
You will be a perfect candidate for the Microsoft Certified: Azure Data Fundamentals certification if you want to:
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Use Azure data services to assess your fundamental understanding of key data principles and how they are applied.
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Revise your knowledge of the fundamentals to pass other Azure role-based certifications like Azure Database Administrator Associate, Azure Data Engineer Associate, Data Analyst Associate, or Azure Developer Associate.
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Microsoft Certified: Customer Data Platform Specialty
This certification will establish your skills and help unlock career opportunities if your area of expertise is developing solutions that offer insight into client profiles and that track engagement activity to help optimize customer experiences and promote customer retention.
Before applying for this certification, you must have practical knowledge of Dynamics 365 Customer Insights, Power Query, Microsoft Dataverse, Common Data Model, Microsoft Power Platform, and one or more additional Dynamics 365 apps. You also require knowledge of privacy, consent, compliance, security, ethical AI, and data retention policy practices. Additionally, you should have knowledge of the KPI, data retention, validation, visualization, preparation, matching, segmentation, and enhancement processes.
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Microsoft Certified: Azure Cosmos DB Developer Specialty
A candidate for this certification should be knowledgeable about developing, applying, and maintaining data management and storage cloud-native apps.
For this certification, a candidate needs to be well-versed in creating apps for Azure and working with Azure Cosmos DB database technology. They must be skilled at creating solutions that use the Azure Cosmos DB for NoSQL API. They should be able to design suitable index policies and write effective SQL queries for the API. They should have prior JavaScript experience building server-side objects. Additionally, they must be knowledgeable in managing and provisioning resources in Azure. They should be able to use PowerShell, read C# or Java code, and understand JSON.
Microsoft Azure Projects for Practice to Enhance Your Portfolio
Though starting a career as a data engineer in Azure is thrilling, it is more complex than acquiring the essential skillset, passing the Azure certification exam, and practicing with Azure interview questions. Most recruiters seek candidates who have real-world data engineering project experience. However, suppose you want your resume for an Azure data engineer position to be shortlisted for further consideration. In that case, you must have a broad understanding of Azure services, data engineering technologies, and processes.
Here are some interesting Azure projects that you can explore to gain practical knowledge and expertise-
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Analyze Yelp Dataset with Spark & Parquet Format on Azure Databricks
This project will teach you to use the Spark and Parquet file formats to explore the Yelp Reviews Dataset. It will help you understand how to use Azure Data Factory to feed data and Azure Databricks to create clusters. Also, it will show you how to deploy the Azure data factory and data pipelines and visualize the analysis as part of this project. This Azure project will teach you about the ETL process, which entails extracting, transforming, and loading data to acquire business insights. This real-world data engineering project has three steps. In the first step, you obtain data from Yelp and use DataFactory to push it to Azure Data Lake. Data preparation is the second stage, and Databricks is used to clean and analyze the data. The final step is to publish your work. You use Databricks to visualize any insights acquired from the raw Yelp data in this stage.
Source Code- Analyse Yelp Dataset with Spark & Parquet Format on Azure Databricks
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Azure Text Analytics for Medical Search Engine Deployment
This project aims to create a machine learning application that can recognize the relationship and pattern between different words used in medical science. It will show you how to construct a clever search engine to look for documents that include those terms. The project also involves developing a machine learning pipeline in Azure to deploy and scale the application. This project will teach you Azure services such as Azure Data Storage, Data Factory, databricks, Azure Containers, etc.
Source Code- Azure Text Analytics for Medical Search Engine Deployment
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Build an Azure Recommendation Engine on Movielens Dataset
This Azure project will show you the usage of Spark SQL to develop a movie recommendation engine using the Movielens dataset. You will learn to create a Big Data pipeline using Azure Data Factory. Also, this project will introduce you to Azure Databricks in this project. You will use Python and Spark to perform data cleaning, analysis, and data transformation. Working on this project will help you learn how to configure Azure Data Lake Storage.
Source Code- Build an Azure Recommendation Engine on Movielens Dataset
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Azure Stream Analytics for Real-Time Cab Service Monitoring
This project intends to create an end-to-end stream processing pipeline for real-time cab service monitoring using Azure Stream Analytics. You will design a real-time streaming data pipeline using the ETL process. Also, learn how to use Event hubs for cab data import and use an Azure VM running a generator code to simulate real-time data. You'll learn how Azure Stream Analytics works and how you can use Azure Monitor.
Source Code- Azure Stream Analytics for Real-Time Cab Service Monitoring
Data and Azure will be the buzzwords in the IT world for years to come. The Microsoft Certified Azure Data Engineer Associate is a career that bridges the gap between these two domains to the greatest extent possible. Although the Azure Data Engineer Certification can help you get ahead of the competition, landing a job requires hands-on experience. Practicing a few good Azure projects will undoubtedly lead to greater chances, better projects, and better companies. Recruiters always look for candidates with good theoretical knowledge and practical experience to showcase their potential.
FAQs
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How hard is Azure Data Engineer Certification?
The Azure Data Engineer Certification is one of the most rigorous and challenging exams. This exam assesses your ability to set up a data processing pipeline and configure each component. It requires you to have a deep knowledge of data computation languages (preferably SQL/Python/Scala), parallel processing, and data architecture patterns.
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What is the most popular Azure Certification?
The Microsoft Certified: Azure Fundamental Exam is the most popular Azure credential (AZ-900). It teaches system administrators and developers the fundamentals of using Windows Azure. You can also learn about cloud computing, networking, storage, privacy, and security, among other topics. It is one of the highest-paying cloud certifications and can help you expand your job prospects.
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What does an Azure data engineer do?
An Azure data engineer manages, distributes, analyzes, organizes, optimizes, and secures the data, using his unique talents and capabilities. Azure data engineers engage with business stakeholders to determine and address data requirements. They also regulate, govern, and guarantee data privacy and security.
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Is Azure good for data engineer?
Microsoft Azure is good for data engineers as they can build any app and deploy it anywhere utilizing their existing skillsets and tools. No matter where their data is stored, they can use Microsoft Azure data engineering to optimize business strategies and leverage its full potential.
About the Author
Daivi
Daivi is a highly skilled Technical Content Analyst with over a year of experience at ProjectPro. She is passionate about exploring various technology domains and enjoys staying up-to-date with industry trends and developments. Daivi is known for her excellent research skills and ability to distill