In this comprehensive guide, we’ll explore how specializing in Microsoft Azure can help your data engineering career.
Here’s what we’ll cover:
The big data industry is booming, especially with the rapid digital transformation that the pandemic has brought on. Companies across industries—from healthcare to retail—are enhancing their big data and analytics practices. LinkedIn lists over 45,000 vacancies for big data jobs in the US. The Bureau of Labor Statistics (BLS) estimates that data-related occupations will grow by 12%, creating 546,200 new jobs by 2028. The big data engineer is among the top paid IT roles with salaries ranging from $130,000 to $222,000. Whichever way you look at it, data engineering is growing to be among the most in-demand careers in 2021.
Naturally, this would mean more qualified professionals would compete for the same jobs and top salaries. When that happens, specialists will find themselves valued more by potential employers, especially for their deep skills and unique problem-solving abilities.
One of the main ways for data engineers to specialize is in the cloud environment, choosing one of the top three providers: Amazon Web Services, Google Cloud Platform, and Microsoft Azure.
Azure is Microsoft’s cloud offerings enabling enterprises to build business apps, serverless computing, data and analytics solutions, and more. 95% of Fortune 500 companies use Azure for a variety of applications, many of them in the areas of big data, machine learning, and AI.
To help big data professionals gain expertise in the Azure platform and build credibility in the job market, Microsoft offers a wide range of certifications across foundational, role-based, and specialist skills.
From the fundamentals of Microsoft 365 to expert qualifications in AI or security engineering, Microsoft offers several certifications under nine categories. The Azure data engineer certification is one of the most sought after. This exam certifies data engineers to “design and implement the management, monitoring, security, and privacy of data using the full stack of data services.”
An active Azure certification can help expand available job opportunities, increase salaries and enable long-term career growth. A recent survey found 93% of decision-makers agree that certified employees provide added value. In fact, over half of the respondents in the study estimate that the annual economic benefit of a certified employee is more than $10,000; 16% estimate the benefit is $30,000 or higher. This reflects on the data engineers’ salaries and growth opportunities too.
“Over half of global IT decision-makers say they expect their organization to invest in Microsoft technology this year,” a report found. Azure is a vital part of this tech stack. A Microsoft data engineer certification becomes extremely valuable when you’re applying for a specialist role in any particular technology—like this Azure databricks engineer role at Cognizant. Certifications in Azure Data Solution (DP-200 & DP-201) demonstrate to the recruiter clearly and confidently that you’re a perfect fit for the job.
91% of respondents said that certification gives them more professional credibility, according to the 2018 Pearson VUE Value of Certification. Naturally, this acts as a plus while looking for new jobs. Take this role at DXC technologies at Quincy, MA, for instance: It specifies that you need the Azure Data Engineering (AZ-200 and AZ-201) and Azure Cloud Developer (AZ-203) certifications to have to get an edge at being shortlisted. Especially among companies that use Azure, this expectation is rather common.
Certification demonstrates the skills and experience you have in any particular area. Therefore, it puts you in a confident negotiating position while discussing salaries with your potential employers. 35% of respondents reported a salary or wage increase after completing an Azure certification. This has a positive impact while looking for new jobs and offers the opportunity to grow within your existing workplace.
At the rate at which technology is evolving, it is often difficult for employers and candidates themselves to know when they’re ready for the next stage of their career. An active certification can serve as proof that you’re ready. Especially associate or expert level certifications show that you are no longer an entry-level or junior-level employee.
While Microsoft requires you to have solid knowledge in various areas of cloud data engineering, it does not ask for a college degree. With some Azure cloud experience and skills in data processing languages, such as SQL, Python, or Scala, and parallel processing/data architecture patterns, you are eligible to take the exam.
Several individuals who participated in a survey pointed out that Microsoft certification is the “most difficult to earn”. Therefore, structured preparation is critical to qualifying for this exam. Here are some things to consider while applying for the Azure data engineer certification.
These are the four key skills measured in the exam as per Microsoft’s official docs. Within each of these, Microsoft tests you for a wide range of skills and experience. You can see the entire skills outline here.
To begin with, explore the online courses that Microsoft itself offers for each skill. The entire learning path is available here for you to plan. There are also several books that offer a detailed look. For instance, ‘Azure Storage, Streaming, and Batch Analytics: A Guide for Data Engineers’ by Richard Nuckolls is a great primer. ‘Data Engineering on Azure’ by Microsoft data engineer Vlad Riscuita is also a useful foundational resource.
However, it is important to understand that none of these can be comprehensive. Most books or online courses are either too broad, covering only the fundamentals, or too narrow, focussing on a specific niche. It often takes aspirants a significant amount of time and energy to navigate these resources and learn what they need.
It is for these reasons that many technologists choose an online bootcamp, like the Springboard Data Engineering Career Track— not only does it offer a comprehensive understanding, but also includes capstone projects, 1:1 mentorship, and a smooth transition to a data engineering career.
The data engineering certification is a practitioner’s exam. Make sure that you have applied all the lessons to practice. Use Microsoft Docs, which also includes code samples and webinar recordings, to understand specific use cases. Take advantage of the Azure architecture center for practical lessons such as how-to guides, best practices, etc. You can also take Microsoft’s practice exams to test your skills.
In most Microsoft exams, there are 40-60 questions. However, this comprises a variety of formats and question types. There is no way to know what your exam might be like; however, you can browse some possibilities here. This also includes the case study format, which asks scenario-based questions reflecting real work that you might be doing on Azure.
The Azure data engineer certification is one of the most difficult exams to pass—given the wide range of concepts, various formats of questions, and the unpredictability of the exam itself. A strong foundation in data engineering can help you earn the certification.
Springboard’s Data Engineering Bootcamp offers precisely that. With a mentor-led, project-driven approach to data engineering, Springboard offers the right mix of foundational knowledge, hands-on experience, and practical skills that help you build a solid career in the field.
Ready to switch careers to data engineering?
Data engineering is currently one of tech’s fastest-growing sectors. Data engineers enjoy high job satisfaction, varied creative challenges, and a chance to work with ever-evolving technologies. Springboard now offers a comprehensive data engineering bootcamp.
You’ll work with a one-on-one mentor to learn key aspects of data engineering, including designing, building, and maintaining scalable data pipelines, working with the ETL framework, and learning key data engineering tools like MapReduce, Apache Hadoop, and Spark. You’ll also complete two capstone projects focused on real-world data engineering problems that you can showcase in job interviews.
Check out Springboard's Data Engineering Career Track to see if you qualify.
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