Top 55 Interview Questions for Microsoft Data Engineers – Blog

Top 55 Interview Questions for Microsoft Data Engineers – Blog

Data engineers are responsible both for managing structured and emerging data types like streaming data. This requires the ability to learn and understand new tools, platforms, procedures, and programming languages such as Python and HDInsight. A Data Engineer requires a high-quality job interview. Testpreptraining has compiled this post with answers to the most frequently asked interview questions.
1. Define data engineering.
Data engineering is a term used in large data. It is the application of data acquisition and analysis. Data from different sources is just not right. Data engineering is a process that transforms this unreliable data into useful data.
2. Explain Azure Data Factory.
Cloud-based integration help makes it possible to create data-driven processes in cloud for data transport and data transformation.
You can schedule and create data-driven processes known as pipelines, which can ingest data form various data stores, while managing the Azure Data Factory.
It might use computing services such as Spark, HDInsight Hadoop and Azure Machine Learning to prepare and mold data.
3. Why did you choose a career in Data Engineering?
This question will be asked by an interviewer to learn more about your motivation and enthusiasm for data engineering as a career. They are looking for people who are passionate about the field. To share their story and highlight what excites the most about being a data engineer certified, the candidate can do this:
4. What do you know about Data Modelling?
Data modeling is the process by which complicated software design is documented as a plan that can be easily understood by anyone. It is a conceptual illustration that combines several data objects with the rules.
5. What is Hadoop streaming?
Hadoop Streaming allows you to take into account the creation of the guide, decrease in employment, and submit them to a particular group.
6. Why do we need Azure Data Factory?
Data is now of great value and comes from many sources. There are a few elements that must be considered when we transmit this data to the cloud.
Data can come in any format as it arrives from different sources. These sources can transport or channelize data in many ways. They can also store it in a unique format. This data must be well maintained when it is transferred to the cloud or selective storage. This means that you will need to modify or remove any undesirable parts from the data. We need to ensure that data is pulled from multiple sources, then we store it in one place. If necessary, we can convert it into something more important.
Data factory is a way to make this complete process more organized and manageable.
7. Name the different types of design schemas in Data Modelling.
Two types of schemas are common in data modeling:
1) Star schema
2) Snowflake schema.
8. Let’s say you are a data engineer within an organization. You are asked to transfer four databases to Microsoft Azure. These databases can be used to perform cross-database queries that retrieve data from different databases. What is the purpose of the Azure data platform you will use to meet your needs?
SQL Server on the Azure virtual machine is the best option to transfer many databases that can work together using cross-database queries.
9. Define integration runtime.
The integration runtime is an estimate infrastructure that Azure Data Factory uses to present the following data integration capabilities across different netws