Azure Data Engineer Interview Questions

Azure, Microsoft’s cloud computing platform, which offers a wide array of services, sync features, and monitoring tools, is establishing itself as a leader in the industry. Due to this, there is a huge demand among tech businesses for data engineers and experts with Azure certifications.

Azure data engineers combine, transform, and consolidate data from numerous structured and unstructured data systems into formats that can be used to create analytics solutions. The data engineers hired by Azure are experts who are highly paid.

In the US, the average annual income for an Azure data engineer is $120,251. Most experienced data engineers can earn up to $143,216 per year, while entry-level occupations start at $116,342 annually.

To succeed in the Azure interview, you must fully grasp all the requirements to become an Azure data engineer. To kickstart your interview prep process, we have shortlisted the top Azure data engineer interview questions.

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To help you crack Azure data engineer interview questions, in this article, we’ll cover:

• Basic Azure Data Engineer Interview Questions and Answers
• Intermediate Azure Data Engineer Interview Questions and Answers
• Advanced Azure Data Engineer Interview Questions and Answers
• FAQs on Azure Data Engineer Interview Questions

Basic Azure Data Engineer Interview Questions and Answers

If you’re someone who’s just starting, here are some basic Azure data engineer interview questions:

1. Define Microsoft Azure.

A cloud computing platform that offers hardware and software both, Microsoft Azure provides a managed service that allows users to access the services that are in demand.

2. List the data masking features Azure has.

When it comes to data security, dynamic data masking has several vital roles and contains sensitive data to a certain specific set of users. Some of its features are:

• It’s available for Azure SQL Database, Azure SQL Managed Instance, and Azure Synapse Analytics.
• It can be carried out as a security policy on all the different SQL databases across the Azure subscription.
• The levels of masking can be controlled per the users' needs.

3. What is meant by a Polybase?

Polybase is used to optimize data ingestion into the PDW and support T-SQL. It lets developers transfer external data transparently from supported data stores, no matter the storage architecture of the external data store.

4. Define reserved capacity in Azure.

Microsoft has included a reserved capacity option in Azure storage to optimize costs. The reserved storage gives its customers a fixed amount of capacity during the reservation period on the Azure cloud.

5. What is meant by the Azure Data Factory?

Azure Data Factory is a cloud-based integration service that lets users build data-driven workflows within the cloud to arrange and automate data movement and transformation. Using Azure Data Factory, you can:

• Develop and schedule data-driven workflows that can take data from different data stores.
• Process and transform data with the help of computing services such as HDInsight Hadoop, Spark, Azure Data Lake Analytics, and Azure Machine Learning.

Sample Basic Azure Data Engineer Interview Questions

1. Explain the main ETL service in Azure.
2. Why is the Azure Data Factory important?
3. What is the limit on the number of integration runtimes?
4. Differentiate between Azure Data Lake and Azure Data Warehouse.
5. Define the integration runtime.

You can also look at these top Data Engineer Interview Questions for practice.

Intermediate Azure Data Engineer Interview Questions and Answers

When applying for intermediate-level roles, these are the Azure data engineer interview questions you can expect:

1. What do you mean by blob storage in Azure?

It is a service that lets users store massive amounts of unstructured object data such as binary data or text. It can even be used to publicly showcase data or privately store the application data. Blog storage is commonly used for:

• Providing images or documents to a browser directly
• Audio and video streaming
• Data storage for backup and restore disaster recovery
• Data storage for analysis using an on-premises or Azure-hosted service

2. Define the steps involved in creating the ETL process in Azure Data Factory.

The steps involved in creating the ETL process in Azure Data Factory are:

• In the SQL Server Database, create a Linked Service for the source data store
• For the destination data store, build a Linked Service that is the Azure Data Lake Store
• For Data Saving purposes, create a dataset
• Build the pipeline and then add the copy activity
• Plan the pipeline by attaching a trigger

3. Define serverless database computing in Azure.

The program code is typically present either on the client-side or the server. However, serverless computing accompanies the stateless code nature, which means the code doesn’t need any infrastructure.

Users have to pay to access the compute resources the code uses within the brief period in which the code is being executed. It's cost-effective, and users need to pay only for the resources they have used.

4. Explain the top-level concepts of Azure Data Factory.

The top-level concepts of Azure Data Factory are as follows:

1. Pipeline

Used as a carrier for the numerous processes taking place. Every individual process is known as an activity.

2. Activities

Activities stand for the process steps involved in a pipeline. A pipeline has one or multiple activities and can be anything. This means querying a data set or transferring the dataset from one source to the other.

3. Datasets

Simply put, it’s a structure that holds the data.

4. Linked Services

Used for storing critical information when connecting an external source.

Check out these articles to prepare for FAANG Data Engineering interviews:

• Amazon Data Engineer Interview Questions
• Facebook Data Engineer Interview Questions

Sample Intermediate Azure Data Engineer Interview Questions

1. Differentiate between HDinsight & Azure Data Lake Analytics.
2. Elaborate on the best way to transfer data from an on-premise database to Azure.
3. Give some ways to ingest data from on-premise storage to Azure.
4. What is data redundancy in Azure?
5. In Azure SQL DB, what are the different data security options available?
6. Define the Azure table storage.
7. What is Azure Databricks, and what separates it from regular data bricks?
8. What is the Azure storage explorer and its uses?
9. List the various kinds of storage in Azure.
10. What are the different kinds of windowing functions in Azure Stream Analytics?

Practice some Azure DevOps interview questions here.

Advanced Azure Data Engineer Interview Questions and Answers

You need to prepare these Azure data engineer interview questions for experienced professionals when applying for more advanced positions:

1. How is a pipeline scheduled?

To schedule a pipeline, you could take the help of the scheduler trigger or the time window trigger. This trigger uses the wall-clock calendar schedule and can plan pipelines at periodic intervals or calendar-based recurring patterns.

2. What’s the significance of the Azure Cosmos DB synthetic partition key?

To distribute the data uniformly across multiple partitions, selecting a good partition key is pretty important. A Synthetic partition key can be developed when there isn’t any right column with properly distributed values.

Here are the three ways in which a synthetic partition key can be created:

1. Concatenate Properties: Combine several property values to create a synthetic partition key.
2. Random Suffix: A random number is added at the end of the partition key's value.
3. Pre-calculated Suffix: Add a pre-calculated number to the end of the partition to enhance read performance.

Read How to Prepare for Data Engineer Interviews to get interview-ready.

3. Which Data Factory version needs to be used to create data flows?

Using the Data Factory V2 version is recommended when creating data flows.

4. How to pass the parameters to a pipeline run?

In Data Factory, parameters are a top-tier concept. They can be defined at the pipeline level, followed by the passing of arguments to execute the pipeline run on-demand or upon using a trigger.

Sample Advanced Azure Data Engineer Interview Questions

1. Can default values for the pipeline parameters be defined?
2. About data flow, what has changed from private preview to limited public preview?
3. What are the two levels of security in ADLS Gen2?
4. What are the data flow partitioning schemes in Azure?
5. What are multi-model databases?

These are some important Azure data engineer interview questions that will give you an idea of what to expect in the interview. Also, ensure that you prepare these topics — Security, DevOps, CI/CD, Infrastructure as a Code best practices, Subscription, Billing Management, etc.

As you prepare for your DE interview, it would be best to study Azure using a holistic approach that extends beyond the fundamentals of the role. Don’t forget to prep your resume as well with the help of the Data Engineer Resume Guide.

Here are some more blogs you can check out to get a better sense of the interview process:

• What Does a Data Engineer Do?
• 15 Skills to Ace Data Engineering Interviews
• The Ultimate Data Engineer Interview Guide

FAQs on Azure Data Engineer Interview Questions

Q1. What does an Azure Data Engineer do?

Azure data engineers are responsible for the integration, transformation, operation, and consolidation of data from structured or unstructured data systems.

Q2. What skills are needed to become an Azure data engineer?

As an Azure data engineer, you’ll need to have skills such as Database system management (SQL or Non-SQL), Data warehousing, ETL (Extract, Transform and Load) tools, Machine Learning, knowledge of programming language basics (Python/Java), and so on.

Q3. How to prepare for the Azure data engineer interview?

Get a good understanding of Azure’s Modern Enterprise Data and Analytics Platform and build your knowledge across its other specialties. Further, you should also be able to communicate the business value of the Azure Data Platform.

Q4. What are the important Azure data engineer interview questions?

Some important questions are as follows:

1. What is the difference between Azure Data Lake Store and Blob storage? 
2. Differentiate between Control Flow activities and Data Flow Transformations. 
3. How is the Data factory pipeline manually executed?

Q5. Are Azure data engineers in demand?

The answer is yes. As per Enlyft, almost 567,824 businesses are using the Azure platform worldwide. This implies that the business and its needs are growing. So, it’s safe to say that Microsoft Azure data engineers are highly in demand.

How to Crack a Data Engineer Interview

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