Azure Data Engineer vs AWS Data Engineer

Introduction

The world of data is growing at an incredible rate, and companies are searching for qualified individuals to analyze it. Therefore, positions such as the Azure Data Engineer, AWS Data Engineer are popular in the job market. But which career path is right for you? So, let’s consider it using an interesting example, and a friendly approach to guide you through it.

Cloud Data Engineering: Career

Let there be two friends, Aditi and Mark. Aditi works at a tech start-up which has selected Microsoft Azure for their cloud requirements. Mark, however, works for an e-commerce company that uses Amazon web service AWS to house enormous amounts of data.

Both Aditi and Mark have interesting, high-visibility careers as data engineers. However, the daily tasks performed, kind of skills involved, and their employment path is quite dissimilar. It is time to discover these differences to determine which approach is better for you to achieve your goals.

Understanding the Roles

Azure Data Engineer: Aditi engages in building and deploying solutions for clients on the Microsoft Azure Cloud. She often uses tools such as Azure Data Factory, Azure Synapse Analytics, and Azure Databricks. These are the tasks of her projects: creation of pipelines, ownership of data lakes, and implementation of proper data storage and security, as well as scalability.

AWS Data Engineer: Mark focuses on the external environment of AWS. He is well acquainted with services such as Amazon Redshift, AWS glue, and Amazon simple storage service, better referred to as S3. Some of his roles are creating data warehouses, data processing and implementing query optimization workflows.

As will be discussed, both roles need a solid understanding of data engineering principles but set their work on different platforms and tools. So, let’s describe the above platforms to find out which of those is more suitable for you.

Azure vs AWS: A Feature Comparison

1. Ease of Use

Azure ecosystem fits right in with Microsoft products like Office 365 and Power BI. If you’re already comfortable with these tools, then maybe Azure could be intuitive.

However, with AWS, you have unmatched scalability and flexibility. It has extensive documentation and nice community support, and therefore it is a popular choice for start-ups as well as for enterprise companies.

2. Tools and Services

• Azure: Azure’s Data Factory and Synapse Analytics, emphasize on simplicity and friendliness for users, which appeals to beginners as they involve drag and drop functionality.
• AWS: It is known for its depth and variety, including specialized options for almost every data need.

3. Market Demand

Azure and AWS are both powerful in markets, but AWS currently leads in cloud adoption. In other words, more AWS jobs globally. But, Azure is gaining a lot of market share, especially in industries that are Microsoft ecosystem dependent.

Skills and Certification

The following skills can show the specialization needed for Azure Data Engineers as well as AWS Data Engineers in relation to the tools and automation that they employ, along with data visualization.

Certifications:

• For Azure: Microsoft Certified – Azure Data Engineer Associate is required.
• For AWS: The AWS Certified Data Analytics – Specialty is very much valued.

Career Growth and Salary

Both jobs have good paying salaries and growth potential. According to industry data:

In the United States:

• Azure Data Engineers range from $110,000 to $135,000.
• AWS Data Engineers is between $115,000 and $145,000 a year.

In India:

• Azure Data Engineers might earn ₹9 00,000 – ₹16, 00,000 per year.
• AWS Data Engineers earn slightly better than this, with an income ranging from ₹10,00,000 to ₹18,00,000 annually.

Both platforms can lead into senior positions like Cloud Architect, Data Science Lead and Engineering Manager.

Real-Life Example

Let’s revisit Aditi and Mark.

Aditi’s company had to integrate their CRM system with its data warehouse. To sync customer data to advanced analytics in Power BI, she used Azure Data Factory to create an easy to use seamless pipeline. She was also familiar with Microsoft’s ecosystem, so she could deliver a project like this more efficiently.

Further, Mark’s team had to process petabytes of transaction data for real time analytics. He automated ETL pipelines, squeezed processing time from 40x to a few seconds, and was playing around with data lakes, SDKs, and serverless API integration. This complex task was possible due to his deep knowledge of the AWS tools.

These examples prove the importance of being platform expert in solving specific business problems.

How to Choose the Right Path

Here are some questions to guide your decision:

1. What’s your background?

As someone familiar with Microsoft products, Azure might seem an easy transition. If you’re interested in start-up and tech stack diversity, AWS could be more rewarding.

2. What’s the market demand in your region?

Research local job trends. While AWS might be bigger in the world, Azure does better in terms of sectors like healthcare, education, and government.

3. What’s your long-term goal?

If you want to become a data architect or a cloud consultant, think about which platform you would like to make your expertise about.

Are you ready to move to the next step in your Data Engineering Journey?

Getting Started: Your First Steps

1. Learn the Basics: Start with free resource on the Azure and AWS platform. Both have extremely, really extensive tutorials and learning paths.
2. Get Certified: Azure Data Engineer Associate or AWS Data Analytics Specialty certifies your skills.
3. Hands-On Practice: Demonstrate your expertise on building projects like a data pipeline or real time analytics dashboard.
4. Join a Community: Be part of some forums, watch some webinars, and network with professionals in the platform you have chosen.

Conclusion: The Choice is yours

While both career paths are great, choose Azure or AWS, it makes no difference. Finding the right platform has to do with answering this question—and it is about matching your skills, interests and career goals with the platform.

If you are truly interested in learning that, Bosscoder Academy is here to be your guide. Together, we’ll teach you to become a highly demanded data engineering professional with our expert led courses, hands-on projects, and personal career mentoring.

Frequently Asked Questions