Top 50 Azure Data Engineering Interview Questions and Answers

 1. What is Azure Data Factory, and what’s it used for?

   Answer: Azure Data Factory (ADF) is a cloud-based data integration service that enables you to create, schedule, and orchestrate data workflows, making it essential for ETL processes across various data sources.

 

 2. Explain Azure Synapse Analytics and how it differs from Azure SQL Database.

   Answer: Azure Synapse Analytics is an analytics service for big data and data warehousing. It handles massive analytical workloads, whereas Azure SQL Database is more optimized for transactional (OLTP) workloads.

 

 3. What are Azure Databricks, and why are they popular?

   Answer: Azure Databricks is a Spark-based analytics platform optimized for Azure, known for simplifying Spark jobs and its seamless integration with Azure services like Data Lake.

 

 4. Can you explain the role of Azure Data Lake Storage?

   Answer: Azure Data Lake Storage (ADLS) is a big data storage solution for high-performance analytics. It’s optimized for handling petabytes of data and used as a data lake in data engineering workflows.

 

 5. What’s the difference between Azure Data Lake Storage Gen1 and Gen2?

   Answer: ADLS Gen2 combines features from Gen1 and Azure Blob Storage. Gen2 offers better performance, enhanced security, and a hierarchical namespace, crucial for organizing data.

 

 6. Why use Azure Stream Analytics?

   Answer: Azure Stream Analytics processes data in real-time, making it ideal for analyzing IoT or event hub data as events happen.

 

 7. What’s a Data Lake, and how does it compare to a Data Warehouse?

   Answer: A data lake stores raw data in its native format, whereas a data warehouse stores processed, structured data. Data lakes offer flexibility, while warehouses are optimized for analytics.

 

 8. How do you monitor data pipelines in Azure Data Factory?

   Answer: ADF has a monitoring dashboard for pipeline, trigger, and activity runs. Azure Monitor can also provide alerts and insights for more comprehensive monitoring.

 

 9. What’s Delta Lake, and how is it related to Databricks?

   Answer: Delta Lake is an open-source storage layer that adds ACID transactions to Spark, enhancing reliability and data quality in Databricks.

 

 10. Explain PolyBase in Azure Synapse.

   Answer: PolyBase enables querying and importing data from external sources using SQL queries, ideal for managing large volumes of data in Synapse.

 

 11. How would you secure data in Azure Data Lake?

   Answer: Use RBAC, encryption at rest, and network security options like private endpoints for a secure data environment.

 

 12. What’s the purpose of Azure Event Hubs in a data engineering setup?

   Answer: Azure Event Hubs is a streaming platform that ingests millions of events per second, making it essential for real-time data ingestion in analytics pipelines.

 

 13. Explain Azure Key Vault’s role in data engineering.

   Answer: Azure Key Vault securely stores keys, secrets, and certificates, which is critical for managing credentials in data engineering projects.

 

 14. What’s a Spark cluster, and why is it essential in Databricks?

   Answer: A Spark cluster is a group of distributed resources for running parallel Spark jobs. Databricks uses these clusters for big data processing.

 

 15. Describe a Linked Service in Azure Data Factory.

   Answer: A Linked Service in ADF is a connection to an external resource, like a database or blob storage, enabling communication between ADF and that resource.

 

 16. How do you integrate Azure DevOps with Databricks?

   Answer: Azure DevOps can be integrated with Databricks for CI/CD. You can version control notebooks and automate deployments across environments.

 

 17. What’s the difference between Blob Storage and Data Lake Storage?

   Answer: Both provide scalable storage, but ADLS Gen2 has hierarchical namespace support, which is optimized for big data analytics, unlike Blob Storage.

 

 18. Explain Synapse Pipelines.

   Answer: Synapse Pipelines offer data movement and transformation capabilities within Azure Synapse, similar to ADF but integrated within the Synapse ecosystem.

 

 19. What is Azure HDInsight?

   Answer: Azure HDInsight is a managed cloud service for open-source big data frameworks like Hadoop, Spark, and Hive, allowing large-scale data processing.

 

 20. How would you handle schema evolution in Databricks?

   Answer: Delta Lake’s schema enforcement features allow flexible data structure changes without sacrificing data quality, making schema evolution manageable.

 

 21. What’s the difference between ETL and ELT?

   Answer: In ETL, data is transformed before loading into the target, while in ELT, raw data is loaded first and then transformed within the target system.

 

 22. Why use Azure SQL Data Warehouse?

   Answer: It’s designed for large-scale analytical workloads and can scale up to petabytes, ideal for massive data warehousing needs.

 

 23. What is Cosmos DB, and why is it useful?

   Answer: Cosmos DB is a globally distributed, multi-model database. Its ability to support multiple data models (like NoSQL) and global distribution makes it versatile.

 

 24. Explain the role of Azure Logic Apps in data workflows.

   Answer: Logic Apps automate workflows between different services, which is useful for triggering events in response to data changes.

 

 25. What’s the use of Azure Functions in data engineering?

   Answer: Azure Functions allow serverless execution of small, discrete functions, ideal for data transformation tasks or triggering workflows in response to events.

 

 26. What is the role of Data Lake Analytics?

   Answer: It’s an on-demand analytics job service where data can be processed using U-SQL without needing a cluster, which simplifies analysis on large datasets.

 

 27. Explain Azure SQL Managed Instance.

   Answer: It’s a managed version of SQL Server in the cloud, combining SQL Server compatibility with cloud benefits like automatic updates.

 

 28. How does Databricks Delta handle upserts?

   Answer: Delta Lake supports upserts with merge statements, allowing you to update existing records or insert new ones as needed.

 

 29. What are Service Principals?

   Answer: Service Principals are identity types in Azure Active Directory that allow applications or automated processes to access Azure resources securely.

 

 30. How can you optimize costs in Azure Synapse Analytics?

   Answer: Optimize costs by using reserved capacity, scaling down or pausing compute during off-peak hours, and controlling data retention in storage.

 

 31. What’s the purpose of Data Bricks notebooks?

   Answer: Databricks notebooks allow collaborative data science and machine learning tasks, with support for languages like Python, Scala, SQL, and R.

 

 32. Explain Data Partitioning in Databricks.

   Answer: Partitioning divides data into segments for faster access and parallel processing, which is key for efficient querying in Databricks.

 

 33. What is Azure Blob Storage used for?

   Answer: Blob Storage is for storing large amounts of unstructured data, such as media files and backups, and serves as a backbone for many big data solutions.

 

 34. Describe Delta Lake’s ACID compliance.

   Answer: Delta Lake adds ACID transactions to data lakes, ensuring data integrity even in the case of concurrent updates or failures.

 

 35. How do you monitor Spark jobs in Databricks?

   Answer: Use the Spark UI, job clusters dashboard, and Databricks’ native monitoring tools to keep track of job performance and troubleshoot issues.

 

 36. Explain the use of Event Grid in data engineering.

   Answer: Event Grid enables event-driven architectures by routing events from services like blob storage to subscribers, like Azure Functions, for processing.

 

 37. What is Azure Machine Learning?

   Answer: Azure Machine Learning is a platform for building, training, and deploying machine learning models at scale, integrated with the Azure ecosystem.

 

 38. How does Power BI connect to Azure Data Lake?

   Answer: Power BI connects to ADLS via dataflows or data connectors, allowing it to pull data for visualization and reporting.

 

 39. What are Azure Monitor and Application Insights?

   Answer: Azure Monitor tracks the performance of your cloud resources, while Application Insights monitors applications for telemetry data.

 

 40. Describe SQL pools in Azure Synapse.

   Answer: SQL pools provide on-demand, distributed data processing and storage, with dedicated and serverless options for handling big data.

 

 41. How does Databricks handle job scheduling?

   Answer: Databricks allows job scheduling through Databricks Jobs, which can be managed directly in the UI or via integration with other scheduling tools.

 

 42. Explain the use of U-SQL in Data Lake Analytics.

   Answer: U-SQL combines SQL and C to process big data in Azure Data Lake Analytics, making it suitable for complex data processing tasks.

 

 43. How would you use Azure Data Explorer?

   Answer: Azure Data Explorer (ADX) is a fast and scalable data analytics service, optimized for log and telemetry data analysis.

 

 44. What’s a data lineage, and why is it important?

   Answer: Data lineage traces data from origin to destination, essential for ensuring data quality and compliance in data engineering.

 

 45. Explain the Data Flow in ADF.

   Answer: Data Flows in ADF provide a no-code ETL approach, allowing transformations in a visual environment with Spark-based execution.

 

 46. What’s a Storage Account in Azure?

   Answer: A storage account provides scalable and durable storage for Azure services, supporting blobs, files, queues, and tables.

 

 47. Describe the use of ADLS in IoT data storage.

   Answer: ADLS is ideal for IoT due to its ability to handle large, unstructured datasets with high ingestion rates.

 

 48. What’s an Integration Runtime in ADF?

   Answer: Integration Runtime (IR) in ADF is the compute infrastructure for data integration, enabling data movement across networks.

 

 49. How do you use Row-Level Security in Azure Synapse?

   Answer: Row-Level Security in Synapse restricts access to rows in tables based on user roles, enhancing data security.

 

 50. What is Azure Purview, and why is it useful?

   Answer: Azure Purview is a unified data governance tool for managing data assets across Azure, enabling data discovery, cataloging, and lineage tracking.

 

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