Azure data engineer role is one of the most demanded jobs today. Here we enlist different roles you can build a career in Azure data engineering!
Data is the biggest superpower in the present times. Collecting the appropriate and relevant data can help businesses drive better decisions. Furthermore, the proper use of information could support improvements in customer service. This has been one of the causes for a sudden rise in demands for data scientists. However, no one points out the significance of a data engineer amidst the noise for data scientists.
You should note that an Azure data engineer is one of the most coveted job roles in the Microsoft Azure landscape. The following discussion would aim at illustrating a guide for Azure data engineer certification. The discussion would focus on crucial aspects such as the path for becoming an Azure data engineer. The discussion would also make an effort to present details about reasons to choose data engineer jobs.
Preparing for a Microsoft Azure certification? Check out our Microsoft Azure Certification Training Courses and give your preparation a new edge.
The next aspects of the discussion include an outline of the basic and role-specific skills for data engineers. Furthermore, the discussion would also reflect on the details of Azure certification for aspiring data engineers. Most important of all, the following discussion would also present the basic job description of an Azure data engineer and expected salary.
The Path Towards an Azure Data Engineer Role
The path for becoming a data engineer on the Microsoft Azure platform leads directly to the role of an Azure data engineer associate. First of all, you should have a clear idea of the Azure fundamentals for starting on this journey. You need to understand the need to appear and qualify two exams for achieving the job role of a data engineer.
Interestingly, you can become a data engineer on the Azure platform with a role-based certification. The eligibility criteria for the certification exam can find a mention later in this discussion. However, for now, we shall note that there are two exams for becoming an Azure data engineer associate. The two exams have the codes DP 200 and DP 201. These new certification exams are the latest entrants among Azure certifications in the new role-based model.
Reasons to Choose Data Engineer Jobs in Azure
As an Azure data engineer, you can pursue the roles of a data analyst and data scientist in a single job. The work of a data engineer involves the management of data workflows and pipelines. One of the formidable highlights about data engineers is the ambiguity regarding their roles concerning data scientists. However, a closer look at the hierarchy of needs in data science clearly shows the significance of data engineers.
Data engineers are responsible for preparing the foundation that data scientists use for their work. Data engineers are responsible for the collection, moving, storing, and preparation of data infrastructure. Then, data scientists could use the infrastructure for learning or optimization. So, you could observe the significance of a data engineer on the Azure platform from these aspects.
Apart from the significance that an Azure data engineer can enjoy, you could find promising job prospects. The prospects are not important only in terms of the remuneration but also the reputation of potential employers for data engineers. Data engineering is an emerging and constantly evolving job that can stand the test of time and trends in computing.
Importance of Azure Data Engineer Certification
You should note that an Azure data engineer is also one of the most coveted job roles in the Microsoft Azure landscape. The following discussion would aim at illustrating a guide for Azure data engineer certification. The discussion would focus on crucial aspects such as the path for becoming an Azure data engineer. The discussion would also make an effort to present details about reasons to choose data engineer jobs.
The next important concern that should drive every candidate is the tangible nature of validation by Azure certifications. To become an Azure data engineer, you need to clear two critical certification exams. These exams prove your capabilities in the special skills needed for data engineering on the Azure platform.
Therefore, you can always have solid proof of your expertise in Azure data engineering. Also, you could choose Azure as a vital platform for pursuing data engineering because of the gradual rise in its popularity. Presently, Azure commands the second position in the cloud service vendor market. That shows promising reasons to go for Azure data engineering jobs.
Basic Skills Required for the Role in Data Engineering
The number of Azure data engineer jobs is rising steadily. So, you should immediately identify all the basic skills for data engineers on the Azure platform. The basic skills are ideal for every data engineer, irrespective of the cloud platform. Here are some of the prominent foundation-level skills for data engineers.
- Candidates aspiring to become Azure data engineer should have an understanding of the evolving data landscape. They should know about the evolution of data systems and their influence on data professionals.
- Candidates should know the differences between on-premises and cloud data solutions. Furthermore, a clear understanding of business use cases of cloud technologies is also favorable.
- Candidates should have a formidable understanding of the job role and responsibilities associated with an Azure data engineer. Also, candidates should have a comprehensive understanding of services on the Azure data platform.
Large data projects can be complex. The projects often involve hundreds of decisions. Multiple people are typically involved, and each person helps take the project from design to production.
Understand how the world of data has changed and how cloud technologies are bringing new opportunities for the business. It will help you learn about the available data platform technologies, and how a Data Engineer can take advantage of this technology for the benefit of the organization.
Top Job Roles in Azure Data Engineering
Roles such as business stakeholders, business analysts, and business intelligence developers are well known and still valuable. As data processing techniques change with technology, new roles are starting to appear. These roles provide specialized skills to help streamline the data engineering process.
In particular, three roles are starting to become common in modern data projects:
- Data Engineer
- Data Scientist
- Artificial Intelligence (AI) Engineer
1. Data Engineer
Data engineers provision and set up data platform technologies that are on-premises and in the cloud. They manage and secure the flow of structured and unstructured data from multiple sources. The data platforms they use can include relational databases, nonrelational databases, data streams, and file stores. Data engineers also ensure that data services securely and seamlessly integrate with other data platform technologies or application services such as Azure Cognitive Services, Azure Search, or even bots.
Explore how the world of data has evolved and how the advent of cloud technologies is providing new opportunities for businesses to explore. You will learn the various data platform technologies that are available, and how a Data Engineer can take advantage of this technology to an organization benefit.
The Azure data engineer focuses on data-related tasks in Azure. Primary responsibilities include using services and tools to ingest, egress, and transform data from multiple sources. Azure data engineers collaborate with business stakeholders to identify and meet data requirements. They design and implement solutions. They also manage, monitor, and ensure the security and privacy of data to satisfy business needs.
The role of a data engineer is different from the role of a database administrator. A data engineer’s scope of work goes well beyond looking after a database and the server where it’s hosted. Data engineers must also get, ingest, transform, validate, and clean up data to meet business requirements. This process is called data wrangling.
A data engineer adds tremendous value to both business intelligence and data science projects. Data wrangling can consume a lot of time. When the data engineer wrangles data, projects move more quickly because data scientists can focus on their own areas of work.
Both database administrators and business intelligence professionals can easily transition to a data engineer role. They just need to learn the tools and technology that are used to process large amounts of data.
2. Data Scientist
Data scientists perform advanced analytics to extract value from data. Their work can vary from descriptive analytics to predictive analytics. Descriptive analytics evaluate data through a process known as exploratory data analysis (EDA). Predictive analytics are used in machine learning to apply modeling techniques that can detect anomalies or patterns. These are an important part of forecast models.
Descriptive and predictive analytics are just one aspect of data scientists’ work. Some data scientists might even work in the realms of deep learning, iteratively experimenting to solve a complex data problem by using customized algorithms.
Anecdotal evidence suggests that most of the work in a data science project is spent on data wrangling and feature engineering. Data scientists can speed up the experimentation process when data engineers use their skills to successfully wrangle data.
3. AI Engineer
AI engineers work with AI services such as Cognitive Services, Cognitive Search, and Bot Framework. Cognitive Services includes Computer Vision, Text Analytics, Bing Search, and Language Understanding (LUIS).
Rather than creating models, AI engineers apply the prebuilt capabilities of Cognitive Services APIs. AI engineers embed these capabilities within a new or existing application or bot. AI engineers rely on the expertise of data engineers to store information that’s generated from AI.
For example, an AI engineer might be working on a Computer Vision application that processes images. This AI engineer would ask a data engineer to provision an Azure Cosmos DB instance to store the metadata and tags that the Computer Vision application generates.
The roles of the data engineer, AI engineer, and data scientist differ. Each role solves a different problem.
- Data engineers primarily provision data stores. They make sure that massive amounts of data are securely and cost-effectively extracted, loaded, and transformed.
- AI engineers add the intelligent capabilities of vision, voice, language, and knowledge to applications. To do this, they use the Cognitive Services offerings that are available out of the box.
- When a Cognitive Services application reaches its capacity, AI engineers call on data scientists. Data scientists develop machine learning models and customize components for an AI engineer’s application.
Each data-technology role is distinct, and each contributes an important part of digital transformation projects.
If you are aspired to build a career in Azure data engineering, we recommend you to validate your skills with Azure data engineer certification. So, take the right decision and get ready to become an Azure Data Engineer. If you are preparing for any other Azure certification, check out our Microsoft Azure Certification Training Courses.
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