Deloitte Azure Developer Interview Questions and Answers

Medallion Architecture is a data processing architecture that involves breaking down data into smaller pieces for easier processing.

• Medallion Architecture involves breaking down data into smaller pieces for easier processing

• It allows for parallel processing of data to improve performance

• Commonly used in big data processing systems like Hadoop and Spark

Spark Architecture is a distributed computing framework that provides an efficient way to process large datasets.

• Spark Architecture consists of a driver program, cluster manager, and worker nodes.

• It uses Resilient Distributed Datasets (RDDs) for fault-tolerant distributed data processing.

• Spark supports various programming languages like Scala, Java, Python, and SQL.

• It includes components like Spark Core, Spark SQL, Spa...read more

Use SQL query to find the second highest salary in employee table

• Use SQL query with ORDER BY and LIMIT to get the second highest salary

• Example: SELECT DISTINCT salary FROM employee ORDER BY salary DESC LIMIT 1, 1

Partitioning in Azure Data Engineer involves dividing data into smaller chunks for better performance and manageability.

• Partitioning can be done based on a specific column or key in the dataset

• It helps in distributing data across multiple nodes for parallel processing

• Partitioning can improve query performance by reducing the amount of data that needs to be scanned

• In Azure Synapse Analytics, you can use ROUND_ROBIN or H

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

Partition key is a field used to distribute data across multiple partitions in a database for scalability and performance.

• Partition key determines the partition in which a row will be stored in a database.

• It helps in distributing data evenly across multiple partitions to improve query performance.

• Choosing the right partition key is crucial for efficient data storage and retrieval.

• For example, in Azure Cosmos DB, partit...read more

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 pr...read more

Implemented Azure-based data analytics solution for a retail company

• Designed and implemented data pipelines using Azure Data Factory

• Utilized Azure Databricks for data processing and analysis

• Developed Power BI dashboards for visualizing insights

• Implemented Azure SQL Database for storing structured data

• Worked closely with stakeholders to gather requirements and ensure solution met business needs

I have worked on a project to migrate on-premises infrastructure to Azure Cloud for a large enterprise.

• Designed and implemented Azure Virtual Networks, Subnets, and Security Groups.

• Utilized Azure Site Recovery for disaster recovery planning.

• Implemented Azure Active Directory for user authentication and access control.

• Utilized Azure DevOps for continuous integration and deployment.

• Optimized costs by implementing Azure R

Designing a data pipeline to process and analyze large volumes of real-time data from multiple sources.

• Identify the sources of data and their formats

• Design a scalable data ingestion process

• Implement data transformation and cleansing steps

• Utilize Azure Data Factory, Azure Databricks, and Azure Synapse Analytics for processing and analysis

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 re

Blob is a storage service for unstructured data, while ADLS is optimized for big data analytics workloads.

• Blob is a general-purpose object storage service for unstructured data, while ADLS is optimized for big data analytics workloads.

• ADLS offers features like file system semantics, file-level security, and scalability for big data analytics, while Blob storage is simpler and more cost-effective for general storage nee...read more

There are three types of triggers available in Azure Data Factory: Schedule, Tumbling Window, and Event.

• Schedule trigger: Runs pipelines on a specified schedule.

• Tumbling Window trigger: Runs pipelines at specified time intervals.

• Event trigger: Runs pipelines in response to events like a file being added to a storage account.