Azure Data Engineer
100+ Azure Data Engineer Interview Questions and Answers

Asked in Diggibyte Technologies

Q. How to choose a cluster to process the data? What is Azure services ?
Choose a cluster based on data size, complexity, and processing requirements.
Consider the size and complexity of the data to be processed.
Determine the processing requirements, such as batch or real-time processing.
Choose a cluster with appropriate resources, such as CPU, memory, and storage.
Examples of Azure clusters include HDInsight, Databricks, and Synapse Analytics.

Asked in Diggibyte Technologies

Q. How to create mount points? How to load data source to ADLS?
To create mount points in ADLS, use the Azure Storage Explorer or Azure Portal. To load data source, use Azure Data Factory or Azure Databricks.
Mount points can be created using Azure Storage Explorer or Azure Portal
To load data source, use Azure Data Factory or Azure Databricks
Mount points allow you to access data in ADLS as if it were a local file system
Data can be loaded into ADLS using various tools such as Azure Data Factory, Azure Databricks, or Azure HDInsight

Asked in Accenture

Q. Which Integration Runtime should we use if we want to copy data from an on-premise database to Azure?
We should use the Self-hosted Integration Runtime (IR) to copy data from on-premise db to Azure.
Self-hosted IR allows data movement between on-premise and Azure
It is installed on a local machine or virtual machine in the on-premise network
Self-hosted IR securely connects to the on-premise data source and transfers data to Azure
It supports various data sources like SQL Server, Oracle, MySQL, etc.
Self-hosted IR can be managed and monitored through Azure Data Factory

Asked in TCS

Q. Explain SQL inner and left joins when tables contain duplicate values.
SQL inner and left join can be used to combine tables with duplicate values based on specified conditions.
Use INNER JOIN to return rows from both tables that have matching values
Use LEFT JOIN to return all rows from the left table and the matched rows from the right table
Handle duplicate values by using DISTINCT or GROUP BY clauses

Asked in Tech Mahindra

Q. What methods do you use to transfer data from on-premises storage to Azure Data Lake Storage Gen2?
Methods to transfer data from on-premises storage to Azure Data Lake Storage Gen2
Use Azure Data Factory to create pipelines for data transfer
Utilize Azure Data Box for offline data transfer
Leverage Azure Storage Explorer for manual data transfer
Implement Azure Data Migration Service for large-scale data migration

Asked in Insight Global Technologies

Q. What is Distributed table in Synapse? How to choose distribution type
Distributed table in Synapse is a table that is distributed across multiple nodes for parallel processing.
Distributed tables in Synapse are divided into distributions to optimize query performance.
There are three distribution types: Hash distribution, Round-robin distribution, and Replicate distribution.
Hash distribution is ideal for joining large tables on a common key, Round-robin distribution evenly distributes data, and Replicate distribution duplicates data on all nodes....read more
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Asked in Insight Global Technologies

Q. What optimization techniques have you applied in projects using Databricks?
I have applied optimization techniques like partitioning, caching, and cluster sizing in Databricks projects.
Utilized partitioning to improve query performance by limiting the amount of data scanned
Implemented caching to store frequently accessed data in memory for faster retrieval
Adjusted cluster sizing based on workload requirements to optimize cost and performance

Asked in TCS

Q. What is ADLS and diff between ADLS gen1 and gen2
ADLS is Azure Data Lake Storage, a scalable and secure data lake solution. ADLS gen2 is an improved version of gen1.
ADLS is a cloud-based storage solution for big data analytics workloads
ADLS gen1 is based on Hadoop Distributed File System (HDFS) and has limitations in terms of scalability and performance
ADLS gen2 is built on Azure Blob Storage and offers improved performance, scalability, and security features
ADLS gen2 supports hierarchical namespace, which enables efficient...read more
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Asked in Insight Global Technologies

Q. What is Dynamic Content in ADF, and how have you used it in previous projects?
Dynamic Content in ADF allows for dynamic values to be passed between activities in Azure Data Factory.
Dynamic Content can be used to pass values between activities, such as passing output from one activity as input to another.
Expressions can be used within Dynamic Content to manipulate data or create dynamic values.
Dynamic Content can be used in various ADF components like datasets, linked services, and activities.
For example, in a pipeline, you can use Dynamic Content to pa...read more

Asked in Diggibyte Technologies

Q. what is Accumulators? what is groupby key and reducedby key?
Accumulators are variables used for aggregating data in Spark. GroupByKey and ReduceByKey are operations used for data transformation.
Accumulators are used to accumulate values across multiple tasks in a distributed environment.
GroupByKey is used to group data based on a key and create a pair of key-value pairs.
ReduceByKey is used to aggregate data based on a key and reduce the data to a single value.
GroupByKey is less efficient than ReduceByKey as it shuffles all the data ac...read more

Asked in Ksolves India Limited

Q. Cte vs subQuery Stored Procedure vs Functions in SQL Left outer join Pyspark optimisation DIA in azure data factory
CTE is used to create temporary result sets, stored procedures are reusable blocks of code, left outer join combines rows from two tables based on a related column
CTE (Common Table Expression) is used to create temporary result sets that can be referenced within a SELECT, INSERT, UPDATE, or DELETE statement.
Stored Procedures are reusable blocks of code that can be executed with a single call. They can accept input parameters and return output parameters.
Left Outer Join combin...read more

Asked in Tech Mahindra

Q. What are the optimization techniques used in Spark?
Optimization techniques in Spark improve performance and efficiency of data processing.
Partitioning data to distribute workload evenly
Caching frequently accessed data in memory
Using broadcast variables for small lookup tables
Avoiding shuffling operations whenever possible
Tuning configuration settings like memory allocation and parallelism

Asked in KPMG India

Q. What steps are involved in fetching data from an on-premises Unix server?
Steps involved in fetching data from an on-premises Unix server
Establish a secure connection to the Unix server using SSH or other protocols
Identify the data source on the Unix server and determine the data extraction method
Use tools like SCP, SFTP, or rsync to transfer the data from the Unix server to Azure storage
Transform the data as needed before loading it into Azure Data Lake or Azure SQL Database

Asked in Diggibyte Technologies

Q. What is serialization? what is broadcast join?
Serialization is the process of converting an object into a stream of bytes for storage or transmission.
Serialization is used to transfer objects between different applications or systems.
It allows objects to be stored in a file or database.
Serialization can be used for caching and improving performance.
Examples of serialization formats include JSON, XML, and binary formats like Protocol Buffers and Apache Avro.

Asked in Diggibyte Technologies

Q. what is the Spark architecture? what is azure sql?
Spark architecture is a distributed computing framework that processes large datasets in parallel across a cluster of nodes.
Spark has a master-slave architecture with a driver program that communicates with the cluster manager to allocate resources and tasks to worker nodes.
Worker nodes execute tasks in parallel and store data in memory or disk.
Spark supports various data sources and APIs for batch processing, streaming, machine learning, and graph processing.
Azure Databricks...read more

Asked in PwC

Q. Explain Databricks and how it differs from ADF.
Data bricks is a unified analytics platform for big data and machine learning, while ADF (Azure Data Factory) is a cloud-based data integration service.
Data bricks is a unified analytics platform that provides a collaborative environment for big data and machine learning projects.
ADF is a cloud-based data integration service that allows you to create, schedule, and manage data pipelines.
Data bricks supports multiple programming languages like Python, Scala, and SQL, while ADF...read more

Asked in Techigai

Q. Describe how you would implement an IF Else activity in your Azure pipeline.
IF Else activity can be implemented using the Switch activity in Azure Data Factory.
Create a Switch activity in your pipeline
Define the condition in the expression field
Add cases for each condition with corresponding activities
Add a default activity for cases that do not match any condition

Asked in KPMG India

Q. What is a semantic layer?
Semantic layer is a virtual layer that provides a simplified view of complex data.
It acts as a bridge between the physical data and the end-user.
It provides a common business language for users to access data.
It simplifies data access by hiding the complexity of the underlying data sources.
Examples include OLAP cubes, data marts, and virtual tables.

Asked in Insight Global Technologies

Q. Have you worked on any real-time data processing projects?
Yes, I have worked on real-time data processing projects using technologies like Apache Kafka and Spark Streaming.
Implemented real-time data pipelines using Apache Kafka for streaming data ingestion
Utilized Spark Streaming for processing and analyzing real-time data
Worked on monitoring and optimizing the performance of real-time data processing systems

Asked in PwC

Q. How do we perform a delta load using ADF?
Delta load in ADF is achieved by comparing source and target data and only loading the changed data.
Use a Lookup activity to retrieve the latest watermark or timestamp from the target table
Use a Source activity to extract data from the source system based on the watermark or timestamp
Use a Join activity to compare the source and target data and identify the changed records
Use a Sink activity to load only the changed records into the target table

Asked in Insight Global Technologies

Q. How do you load data into Synapse from Databricks?
You can load data from Databricks to Synapse using PolyBase or Azure Data Factory.
Use PolyBase to load data from Databricks to Synapse by creating an external table in Synapse pointing to the Databricks data location.
Alternatively, use Azure Data Factory to copy data from Databricks to Synapse by creating a pipeline with Databricks as source and Synapse as destination.
Ensure proper permissions and connectivity between Databricks and Synapse for data transfer.

Asked in KPMG India

Q. What are the differences between ADLS Gen1 and Gen2?
ADLS gen 2 is an upgrade to gen 1 with improved performance, scalability, and security features.
ADLS gen 2 is built on top of Azure Blob Storage, while gen 1 is a standalone service.
ADLS gen 2 supports hierarchical namespace, which allows for better organization and management of data.
ADLS gen 2 has better performance for large-scale analytics workloads, with faster read and write speeds.
ADLS gen 2 has improved security features, including encryption at rest and in transit.
AD...read more

Asked in KPMG India

Q. What are your current responsibilities as an Azure Data Engineer?
As an Azure Data Engineer, my current responsibilities include designing and implementing data solutions on Azure, optimizing data storage and processing, and ensuring data security and compliance.
Designing and implementing data solutions on Azure
Optimizing data storage and processing for performance and cost efficiency
Ensuring data security and compliance with regulations
Collaborating with data scientists and analysts to support their data needs

Asked in Deloitte

Q. What are the differences between Data Lake Storage Gen1 and Gen2?
Data Lake Gen1 is based on Hadoop Distributed File System (HDFS) while Gen2 is built on Azure Blob Storage.
Data Lake Gen1 uses HDFS for storing data while Gen2 uses Azure Blob Storage.
Gen1 has a hierarchical file system while Gen2 has a flat file system.
Gen2 provides better performance, scalability, and security compared to Gen1.
Gen2 supports Azure Data Lake Storage features like tiering, lifecycle management, and access control lists (ACLs).
Gen2 allows direct access to data ...read more

Asked in Techigai

Q. Sql queries using window functions
Window functions are used to perform calculations across a set of rows in a table.
Window functions are used to calculate values based on a subset of rows within a table
They are used to perform calculations such as running totals, ranking, and moving averages
Examples of window functions include ROW_NUMBER(), RANK(), and SUM() OVER()

Asked in Insight Global Technologies

Q. Have you worked on any Data Validation Framework?
Yes, I have worked on developing a Data Validation Framework to ensure data accuracy and consistency.
Developed automated data validation scripts to check for data accuracy and consistency
Implemented data quality checks to identify and resolve data issues
Utilized tools like SQL queries, Python scripts, and Azure Data Factory for data validation
Worked closely with data stakeholders to define validation rules and requirements

Asked in Insight Global Technologies

Q. How would you set up an ETL flow for data present in a Lake House using Databricks?
Set up ETL flow for data in Lake House using Databricks
Connect Databricks to Lake House storage (e.g. Azure Data Lake Storage)
Define ETL process using Databricks notebooks or jobs
Extract data from Lake House, transform as needed, and load into target destination
Monitor and schedule ETL jobs for automated data processing

Asked in Insight Global Technologies

Q. Write a SQL query to fetch the Top 3 revenue generating Product from Sales table
SQL query to fetch Top 3 revenue generating Products from Sales table
Use the SELECT statement to retrieve data from the Sales table
Use the GROUP BY clause to group the data by Product
Use the ORDER BY clause to sort the revenue in descending order
Use the LIMIT clause to fetch only the top 3 revenue generating Products

Asked in Cognizant

Q. How do you copy multiple tables from on-premise to Azure Blob Storage?
Use Azure Data Factory to copy multiple tables from on-premises to Azure Blob Storage
Create a linked service to connect to the on-premises data source
Create datasets for each table to be copied
Create a pipeline with copy activities for each table
Use Azure Blob Storage as the sink for the copied tables

Asked in TCS

Q. Tell me about a difficult problem you encountered and how you resolved it.
Encountered a data corruption issue in Azure Data Lake Storage and resolved it by restoring from a backup.
Identified the corrupted files by analyzing error logs and data inconsistencies
Restored the affected data from the latest backup available
Implemented preventive measures such as regular data integrity checks and backups
Collaborated with the Azure support team to investigate the root cause
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