Career Spotlights:
Azure Data Engineer
Whatever the Microsoft Cloud role, use our guide to benchmark your salary or contact rate, or to uncover what you should be paying employees in your team.
How much do Azure Data Engineers make?
| First quartile | Median | Third quartile | Contract rate | |
|---|---|---|---|---|
| United States ($) | 125,000 | 150,000 | 180,000 | 110-150 (p/h) |
| United Kingdom (£) | 46,000 | 65,000 | 90,000 | 500-850 (p/d) |
United States ($)
| First quartile | 125,000 |
|---|---|
| Median | 150,000 |
| Third quartile | 180,000 |
| Contract rate (p/h) | 110-150 (p/h) |
United Kingdom (£)
| First quartile | 46,000 |
|---|---|
| Median | 65,000 |
| Third quartile | 90,000 |
| Contract rate (p/d) | 500-850 (p/d) |
57%
of Azure Data Engineers are satisfied with their job, down from 71% in our previous survey*
56%
of Azure Data Engineers are satisfied with their salary, up from 50% in our last survey
39 hours
Permanent Azure Data Engineers work an average of 39 hours per week
40 hours
Freelance Azure Data Engineers work an average of 40 hours per week**
* Comparisons to the survey data in our last study are indicative only due to a limited number of Azure Data Engineers participating.
** A limited number of freelance Azure Data Engineers participated in our survey, so results are indicative only.
What factors impact your earning potential as an Azure Data Engineer?
| Important | Neutral | Unimportant | |
|---|---|---|---|
| Years of technical experience with Microsoft products | 94% | 6% | 0% |
| Years of experience in IT | 94% | 2% | 4% |
| Exposure to large projects | 88% | 10% | 2% |
| Specific vertical industry experience | 65% | 23% | 13% |
| Microsoft certifications | 57% | 14% | 29% |
| Working with AI | 54% | 21% | 25% |
| College/University degree(s) | 49% | 29% | 22% |
Years of technical experience with Microsoft products
| Important | Neutral | Unimportant |
|---|---|---|
| 94% | 6% | 0% |
Years of experience in IT
| Important | Neutral | Unimportant |
|---|---|---|
| 94% | 2% | 4% |
Exposure to large projects
| Important | Neutral | Unimportant |
|---|---|---|
| 88% | 10% | 2% |
Specific vertical industry experience
| Important | Neutral | Unimportant |
|---|---|---|
| 65% | 23% | 13% |
Microsoft certifications
| Important | Neutral | Unimportant |
|---|---|---|
| 57% | 14% | 29% |
Working with AI
| Important | Neutral | Unimportant |
|---|---|---|
| 54% | 21% | 25% |
College/University degree(s)
| Important | Neutral | Unimportant |
|---|---|---|
| 49% | 29% | 22% |
Our key findings report contains highlights from this year’s Careers and Hiring Guide, plus our salary tables to allow you to compare your compensation or benchmark your teams’ salaries or rates no matter their role in the Microsoft ecosystem.
What steps should you take to become an Azure Data Engineer?
Education
The majority (94%) of Azure Data Engineers hold at least a Bachelor’s degree. However, only 27% consider a degree to be important to work with Microsoft Cloud, while 49% believe a degree to be an important factor when it comes to increasing earning potential.
Certification
Close to two-thirds (65%, down 68% from our previous survey) of Azure Data Engineers are certified and 44% (down from 59%) of those have undergone certification renewal to maintain their Microsoft Certified status. This trend of favoring initial certification over renewal is also observed in our wider sample (see here for more information). Meanwhile, 78% (down from 88%) of certified data engineers believe certification enhances their professional value.
Aspiring Azure Data Engineers can begin with the Microsoft Certified: Azure Data Fundamentals certification to strengthen their basic knowledge, and then progress to the Microsoft Certified: Azure Data Engineer Associate for more intermediate-level expertise.
Top Microsoft certifications held by Azure Data Engineers
| Microsoft Certified: Power BI Data Analyst Associate | 38% |
| Microsoft Certified: Azure Data Engineer Associate | 28% |
| Microsoft Certified: Azure Data Fundamentals | 28% |
| Microsoft Certified: Azure Fundamentals | 25% |
| Microsoft Certified: Power Platform Fundamentals | 13% |
| Microsoft Certified: Azure AI Fundamentals | 13% |
Paths to becoming an Azure Data Engineer
There’s no single path that is guaranteed to lead you to a role as an Azure Data Engineer. Data is a major part of any business today, meaning a career in data engineering can begin almost anywhere. However, professionals often transition from roles in data management or analysis, where they build foundational skills for designing and managing data pipelines on Azure.
Here are some of the common starting roles for those who move into data engineering:
Data Analyst: Familiarity with data handling, analysis, and reporting can be a stepping stone to data engineering
Junior Data Engineer: Experience in data pipeline building and ETL processes can provide a good foundation for a Data Engineer role
Database Administrator: Experience in managing and optimizing data storage, databases, and querying aligns with key parts of Azure data engineering
Software Engineer: Engineers familiar with data processing, databases, and cloud services often find it easier to transition into data engineering
Data Analysts, Junior Data Engineers, and Database Administrators often progress into Azure Data Engineering. Familiarity with data management, data integration, and Azure’s data services (like Azure Data Factory and SQL Database) are key assets. However, there are a number of ways to become an Azure Data Engineer, especially when equipped with targeted expertise and essential certifications.
What skills and experience should Azure Data Engineers have?
- Solid experience with managing and storing both structured and unstructured data
- Proficient in ETL processes (extract, transform, load) and tools such as Xplenty, Stitch, and Alooma
- Strong knowledge of data architecture design, deployment, and maintenance
- Expertise in writing ETL logic
- Familiarity with scripting and programming languages like R, Python, Java, and Scala
- Solid understanding of SQL and NoSQL databases and the ability to query them
- Experience with creating and managing data stores and database administration
- Knowledge of big data tools like Hadoop, Hive, Apache Spark, and Kafka
- Proficient in developing complex data pipelines
- Familiarity with machine learning concepts
- Understanding of operating systems such as UNIX, Linux, and Solaris
- Familiarity with data platform technologies such as Azure API Apps, Azure Cognitive Services, and Azure Search
- A strong grasp of algorithms and data structures
