The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice. The global pandemic accelerated the digital transformation, leading to increased demand for data and analytics professionals across industries, such as healthcare and retail.
The Bureau of Labor Statistics (BLS) predicts substantial job growth in data-related professions, with an expected increase of 546,200 jobs by 2028, representing a 12% growth rate. Data engineering is expected to be among the most sought-after professions in 2024 and beyond. Also, the role of an Azure Data Engineer is highly relevant and in demand.
In the post, we will investigate how to become an Azure data engineer, the skills required, the roles and responsibilities of an Azure data engineer, and much more.
Who is an Azure Data Engineer?
The Microsoft Certified Data Engineer is in charge of designing the entire architecture of the data flow while taking the needs of the business into account. To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Storage, Azure Data Lake, Azure Blob Storage, Azure Cosmos DB, Azure Stream Analytics, Azure HDInsight, and other Azure data services are just a few of the many Azure data services that Azure data engineers deal with.
An Azure Data Engineer locates and resolves difficult data-related issues, enhances the performance and scalability of data solutions, and works cooperatively with other teams to develop solutions. They work with various stakeholders to provide real-time data analytics, maintain data quality and integrity, and deliver insightful data to the business.
The main duties of an Azure Data Engineer are planning, developing, deploying, and managing the data pipelines. Additionally, they convert data into formats that can be used and store it effectively and securely in the Azure cloud. The data engineers are responsible for creating conversational chatbots with the Azure Bot Service and automating metric calculations using the Azure Metrics Advisor.
Data engineers must know data management fundamentals, programming languages like Python and Java, cloud computing and have practical knowledge on data technology. Microsoft Certified Azure Data Engineer Associate certification is a fantastic way to demonstrate your expertise to potential employers.
Why Choose Azure Data Engineer?
Given the growing demand for data specialists, the future of Azure Data Engineers looks bright. The demand for Azure Data Engineers is anticipated to rise as more enterprises use cloud-based data solutions. Building, installing, and managing data solutions on the Azure platform will be their responsibility. They will work with other data specialists to ensure that data solutions are successfully integrated into business processes.
Azure Data Engineers will be more crucial than ever in creating and deploying data solutions that make use of emerging machine learning and artificial intelligence technology.
According to Markets and Markets analysis, the size of the worldwide data engineering market is predicted to reach $6.8 billion by 2026. 80% of businesses said that their data-driven activities are crucial or vital to their overall company strategy.
According to Ambition Box, the average yearly income for an Azure Data Engineer is 7 LPA, with a salary range of 5 to 15 LPA. According to these figures, the demand for knowledgeable Azure Data Engineers is projected to increase in the upcoming years. Due to the enormous growth of Azure Cloud, the field of Azure Data Engineering is quickly expanding. Large volumes of data are still being stored on the cloud by businesses, and it is anticipated that the need for qualified individuals to manage and derive insights from this data will increase. As a result, choosing to become a professional data engineer may be a good choice.
How to Become an Azure Data Engineer?
Jobs for Azure data engineers are becoming more and more common. As a result, you must right away list all the fundamental abilities needed by data engineers on the Azure platform. No matter the cloud platform, all data engineers should have the fundamental abilities. Here are a few well-known foundational abilities on how to become an Azure engineer.
- Candidates who want to work as Azure data engineers should be familiar with the changing data landscape. They must be aware of the development of data systems and how it has affected data specialists.
- The distinctions between on-premises and cloud data solutions should be understood by candidates. It is also advantageous to have a thorough understanding of the business applications of cloud technologies.
- The job position and duties related to the role should be thoroughly understood by candidates. Candidates should also have a thorough knowledge of Azure services.
Path Towards Becoming an Azure Data Engineer
Let us look into the structured path on how to become azure data engineer involves a structured path that includes education, skill development, practical experience, and certification. Here is a step-by-step guide on how to become an Azure Data Engineer:
1. Understanding SQL
You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer. To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. You should be able to create intricate queries that use subqueries, join numerous tables, and aggregate data. You should also be able to create indexes and create effective data structures to optimize queries.
2. Data Modeling
The process of creating a logical and physical data model for a system is known as data modeling. Understanding data modeling concepts like entity-relationship diagrams, data normalization, and data integrity is a requirement for an Azure Data Engineer. You ought to be able to create a data model that is performance- and scalability-optimized.
3. Programming and Scripting Skills
Building data processing pipelines requires knowledge of and experience with coding in programming languages like Python, Scala, or Java. You should be able to create scalable, effective programming that can work with big datasets.
4. Database Knowledge
Data warehousing ideas like the star and snowflake schema, as well as how to design and develop a data warehouse, should be well understood by you. This involves knowing how to manage data partitions, load data into a data warehouse, and speed up query execution.
5. Data Integration and ETL
The process of obtaining data from diverse sources, processing and cleaning it, and then loading it into a data warehouse is known as ETL (Extract, Transform, Load). You must be able to create ETL pipelines using tools like Azure Data Factory and write custom code to extract and transform data if you want to succeed as an Azure Data Engineer.
6. Big Data Technologies
You must explore big data technologies such as Apache Spark, Hadoop, and related Azure services like Azure HDInsight. Learn how to process and analyze large datasets efficiently. Master data integration techniques, ETL processes, and data pipeline orchestration using tools like Azure Data Factory. Also, understand how to extract, transform, and load data from various sources.
7. Azure Services
You must be well-versed in a variety of Azure services, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Analysis Services, Azure Stream Analytics, and Azure Data Lake Storage, in order to succeed as an Azure Data Engineer. Understanding how to manage and integrate these services with other Azure services as well as configure them is part of this.
8. Data Security and Compliance
Familiarize yourself with data security best practices, encryption, access controls, and compliance standards, especially if you are working with sensitive or regulated data.
9. Certifications
Consider pursuing certifications that validate your Azure data engineering skills. The Microsoft Certified Azure Data Engineer Associate (DP-203) certification is a notable choice. Cloud Computing prerequisites will help you know how to go about the whole process of certifications and courses.
Skills to Become an Azure Data Engineer
You must specialize in role-specific abilities to land attractive Azure data engineer jobs. The role-specific skills emphasize the fundamental skills and knowledge that a data engineer needs in order to complete their responsibilities.
- You should possess a strong understanding of data structures and algorithms.
- To comprehend the database and the underlying architecture, you ought to grasp SQL.
- Additionally, applicants seeking data engineer positions should be aware that most tools for data processing and storage use programming languages. Therefore, it is essential to have a thorough understanding of programming languages like Python, Java, or Scala.
- Data engineers must therefore have a thorough understanding of programming languages like Python, Java, or Scala.
- Candidates looking for Azure data engineering positions should also be familiar with big data tools like Hadoop.
- Finally, prominent mentions of distributed systems and data pipelines are included in role-specific abilities for data engineers.
Skills Needed to Become an Azure Data Engineer Specialist
As an Azure data engineer specialist, you must have role-specific abilities to land attractive Azure data engineer jobs. The role-specific skills emphasize the fundamental skills and knowledge that a data engineer needs in order to complete their responsibilities.
- Awareness of Evolving Data Landscape: You should stay informed about the ever-evolving data landscape, including emerging technologies, trends, and best practices in data management, storage, and processing.
- Understanding On-Premises vs. Cloud Data Solutions: Recognizing the differences between on-premises and cloud data solutions is crucial. Cloud solutions offer scalability, flexibility, and cost-efficiency compared to traditional on-premises setups.
- Business Applications of Cloud Technologies: Understanding cloud computing prerequisites and aligning cloud solutions with specific business needs and goals is essential for any data engineer working in a cloud-based environment.
- Comprehensive Knowledge of Azure Services: Being well-versed in Microsoft Azure services, including data-related services like Azure SQL Database, Azure Data Factory, and Azure Data Lake Storage, is critical for Azure Data Engineers.
- Programming Languages: Proficiency in programming languages like Python, Java, or Scala is important for data engineers, as these languages are commonly used for data manipulation and transformation.
- SQL Proficiency: SQL (Structured Query Language) is fundamental for working with databases. Data engineers should have a solid understanding of SQL for querying and managing data in relational databases.
- ETL Processes: Knowledge of ETL (Extract, Transform, Load) processes and familiarity with ETL tools like Xplenty, Stitch, and Alooma is essential for efficiently moving and processing data.
- Data Lake vs. Data Warehouse: Understanding when to use a data lake or a data warehouse based on the specific needs of a business is crucial for optimizing data storage and processing.
- Automation: Automation is key for managing large datasets efficiently. Data engineers should be proficient in scripting to automate routine data tasks and workflows.
- Machine Learning Awareness: While data engineers aren't primarily focused on machine learning, having a basic understanding of machine learning concepts can facilitate collaboration with data scientists.
- Big Data Technologies: Familiarity with Big Data tools and technologies like Hadoop, MongoDB, and Kafka is important, especially when dealing with large volumes of data.
- Cloud Services: As businesses increasingly migrate to the cloud, data engineers should be knowledgeable about cloud technologies and services, including Azure, for data storage and processing.
- Data Security: Data engineers often play a role in data security by implementing access controls and encryption measures to protect data.
- Stay Informed About Azure Updates: Being informed about updates, features, and changes in Azure's data-related services is vital for keeping Azure data solutions current and effective.
Azure Data Engineer Exam Details
If you wish to pursue a career as an Azure data engineer, you should pass the DP-203 exam. To answer this exam, you need to be well-versed in languages used for data processing, such as SQL, Python, and Scala, as well as in parallel processing and data architectural patterns. You should be skilled in building data processing solutions using Azure Data Factory, Azure Synapse Analytics, Azure Stream Analytics, Azure Event Hubs, Azure Data Lake Storage, and Azure Databricks.
By passing the Microsoft Certified - Azure Data Engineer Associate exam, you will be better able to demonstrate the necessary foundational knowledge and hands-on experience for working with data on Microsoft Azure. The Data Engineering on Microsoft Azure (DP-203) certification exam assesses your technical proficiency from designing and implementing data storage to developing data processing to securing, monitoring, and optimizing data storage and processing. The certification cost is $165 USD. This is a proctored exam with 40 to 60 multiple choice questions to be answered in a duration of 150 minutes.
Azure Data Engineer Exam Retake Policy
Microsoft Learn offers certification renewal service without any cost. The certification is valid for one year and six months before the certificate's expiration, the renewal period begins. You have a limited amount of time before the certificate expires to complete a free online assessment and extend the certificate by one year from its current expiration date.
Certification Needed for a Job in Azure Data Engineering
Because they offer verifiable proof of your knowledge and ability in this profession, certifications can be very helpful in helping you land a position in Azure Data Engineering. Data engineering is one of many Azure occupations for which Microsoft Azure offers a range of certifications. For a career in Azure Data Engineering, the following important certifications are important to have:
- Microsoft Certified: Azure Data Engineer Associate (DP-203): Data engineering on the Azure platform is the primary focus of this certification. By achieving DP-203 certification, you will demonstrate that you are an expert in applying Azure services to create and deploy data storage, data processing, and data security solutions.
- Microsoft Certified: Azure Fundamentals (AZ-900): Although not being specifically related to data engineering, AZ-900 certification offers a baseline understanding of Azure services, which can be useful, especially if you are new to Azure. Before obtaining more specific certificates, it might act as a starting point.
- Microsoft Certified: Azure Administrator Associate (AZ-104): The management of Azure resources, including those involved in data engineering, is the responsibility of Azure administrators. If you manage and maintain Azure environments, Az-104 certification may be beneficial to you.
- Microsoft Certified: Azure AI Engineer Associate (AI-102): If your data engineering work involves integrating AI and machine learning into your solutions, AI-102 certification can be valuable. It covers various aspects of AI implementation on Azure.
- Microsoft Certified: Azure DevOps Engineer Expert (AZ-400): DevOps practices are increasingly important in data engineering for automating deployment, testing, and continuous integration/continuous deployment (CI/CD). AZ-400 certification focuses on Azure DevOps and can be relevant in this context.
- Microsoft Certified: Azure Solutions Architect Expert (AZ-303 and AZ-304): Azure Solutions Architects are responsible for designing complex solutions, including those related to data engineering. While not data engineering-specific, Azure Solutions Architect certification can be valuable if you are involved in architecture and design aspects.
Salary of Azure Data Engineer Experts
Country
| Base Salary per Year
| Range Yearly
|
|---|
USA
| $130,982
| $117,000 to $160,000
|
India
| ₹830,000
| ₹530,000 to ₹1,200,000
|
Australia
| A$105,000
| A$90,000 to A$120,000
|
UK
| £56,000
| £46,000 to £69,000
|
Germany
| €70,000
| €58,000 to €78,000
|
Conclusion
To wrap it up, data is indeed an indispensable asset for companies, and Azure Data Engineers play a crucial role in ensuring that this data is managed, integrated, and made accessible for building analytics solutions. These highly skilled specialists are responsible for designing the data architecture, considering the specific needs and goals of the business. Additionally, their collaboration with Azure AI services enhances the value they can provide to end-users by offering pre-built models and leveraging Azure's cognitive capabilities. In the evolving world of data-driven decision-making, Azure Data Engineers are pivotal in helping organizations harness the power of their data for insights and innovation. KnowledgeHut Microsoft certified Azure Data Engineer Associate certification will guide you to use azure data platform to implement analytical solutions and design and optimize data platforms that meet data pipeline needs.
