Azure Data Engineer Interview Questions and Answers for Freshers

🔹 Basics of Azure & Data Engineering (1–20)

1. What is Microsoft Azure?
   A cloud computing platform offering services like storage, compute, databases, and analytics.

2. What is Azure Data Engineer?
   A professional who builds, manages, and optimizes data pipelines and data flows in the Azure environment.

3. What are the main responsibilities of an Azure Data Engineer?

   • Design and implement data pipelines
   • Transform data
   • Store and manage structured/unstructured data
   • Optimize performance and cost

4. What is a data pipeline?
   A series of steps that process and move data from one system to another.

5. Name some Azure services used by Data Engineers.

   • Azure Data Factory
   • Azure Synapse Analytics
   • Azure Data Lake Storage
   • Azure Databricks
   • Azure Stream Analytics

6. What is Azure Data Factory (ADF)?
   A cloud-based data integration service for creating ETL and ELT pipelines.

7. What is Azure Synapse Analytics?
   An analytics service that combines big data and data warehousing.

8. What is Azure Data Lake?
   A scalable data storage and analytics service for big data workloads.

9. Difference between Azure Data Lake Gen1 and Gen2?

   • Gen2 supports hierarchical namespace and integrates with Blob storage.
   • Gen1 is older and less secure.

10. What is Azure Databricks?
    An Apache Spark-based analytics platform optimized for Azure.

11. What is structured, semi-structured, and unstructured data?

• Structured: Tables
• Semi-structured: JSON, XML
• Unstructured: Images, videos

12. What is the use of Azure Blob Storage?
    To store large amounts of unstructured data.

13. What is the difference between Azure Blob and Azure Data Lake?

• Blob: General storage
• ADLS: Optimized for big data

14. What is a linked service in ADF?
    Defines the connection to data sources.

15. What are datasets in ADF?
    Represents data structure used in the pipeline.

16. What is a pipeline in ADF?
    A logical group of activities that perform a unit of work.

17. What are triggers in ADF?
    Used to schedule pipeline executions.

18. What is Integration Runtime (IR) in ADF?
    The compute infrastructure for data movement and transformation.

19. What is an activity in ADF?
    Represents a processing step in a pipeline.

20. What is ETL vs ELT?

• ETL: Extract, Transform, Load
• ELT: Extract, Load, Transform (optimized for cloud)

🔹 Azure Data Factory (ADF) Deep Dive (21–40)

21. What types of triggers are available in ADF?

• Schedule
• Tumbling window
• Event-based

22. Can we copy data from on-prem to cloud using ADF?
    Yes, using Self-hosted IR.

23. What is a self-hosted integration runtime?
    Used to move data between on-prem and cloud securely.

24. What is Data Flow in ADF?
    Visually-designed data transformation logic.

25. What is the difference between Mapping and Wrangling Data Flow?

• Mapping: Graphical transformations
• Wrangling: Data prep like Power Query

26. What are the different types of activities in ADF?

• Data movement
• Data transformation
• Control activities

27. How do you monitor pipeline executions?
    Via the Monitor tab in ADF.

28. Can ADF run stored procedures?
    Yes, using Stored Procedure Activity.

29. What is ADF CI/CD?
    Continuous Integration and Deployment using Git and Azure DevOps.

30. Can you call REST APIs in ADF?
    Yes, using Web activity.

31. How do you secure credentials in ADF?
    Using Azure Key Vault integration.

32. What is a ForEach activity in ADF?
    Iterates over a collection.

33. How to copy data from Azure Blob to SQL in ADF?
    Using Copy Data Activity with source and sink linked services.

34. Can ADF be integrated with Git?
    Yes, ADF supports GitHub and Azure Repos.

35. How to handle errors in ADF pipelines?
    Using activity dependencies and custom logging.

36. What is parameterization in ADF?
    Making pipelines dynamic using parameters.

37. How do you pass parameters to pipelines?
    Through JSON payload at trigger or REST API.

38. What are ARM templates in ADF?
    Templates used to deploy ADF components.

39. Can you use Lookup activity in ADF?
    Yes, to retrieve data for use in other activities.

40. What are expressions in ADF?
    Used for dynamic content using pipeline functions.

🔹 Azure Data Lake, Blob & Storage (41–60)

41. What is Azure Blob Storage?
    A scalable object storage for unstructured data.

42. What are blob tiers?

• Hot
• Cool
• Archive

43. What is the difference between Block Blob and Append Blob?

• Block: Optimized for write-once, read-many
• Append: Optimized for append operations

44. How do you mount ADLS in Azure Databricks?
    Using dbutils.fs.mount

45. What is hierarchical namespace in ADLS Gen2?
    Supports folders and directory-level operations.

46. How do you secure Azure Data Lake?

• RBAC
• ACLs
• SAS Tokens

47. What is a container in Blob Storage?
    A logical unit for organizing blobs.

48. How do you upload data to Blob?
    Using Azure Portal, CLI, or SDK.

49. What is Azure Storage Explorer?
    A tool to manage storage accounts and blobs.

50. What is versioning in Azure Storage?
    Maintains previous versions of blobs.

🔹 Azure Synapse & Databricks (61–80)

51. What is Azure Synapse Analytics?
    A cloud-based data warehouse and big data solution.

52. What are dedicated SQL pools?
    Provisioned compute resources for data warehousing.

53. What is serverless SQL pool?
    Query data in Data Lake without provisioning compute.

54. What is PolyBase in Synapse?
    Used to query external data from SQL.

55. What is the difference between Synapse and Databricks?

• Synapse: Optimized for SQL
• Databricks: Optimized for Spark & ML

56. What is a workspace in Synapse?
    Centralized interface for managing resources.

57. What is a Spark pool in Synapse?
    Apache Spark compute engine in Synapse.

58. What is Azure Databricks used for?
    Big data analytics, machine learning, and ETL.

59. How do you read a CSV file in Databricks?

60. What languages are supported in Databricks?

• Python
• Scala
• SQL
• R

🔹 SQL, Performance, and Security (81–100)

61. What is a SQL stored procedure?
    A precompiled collection of SQL statements.

62. What is indexing in SQL?
    Improves query performance by speeding up data retrieval.

63. What is partitioning in data processing?
    Dividing data into segments for parallel processing.

64. What is schema-on-read vs schema-on-write?

• Read: Schema applied at query time
• Write: Schema enforced when writing data

65. What is data lineage?
    Tracking the origin and flow of data through pipelines.

66. What is GDPR and why is it important?
    Data privacy regulation that affects how data is handled.

67. What is encryption at rest vs in transit?

• At rest: Stored data
• In transit: During data transfer

68. What is Azure Key Vault?
    Manages secrets, certificates, and keys securely.

69. How do you monitor ADF pipeline performance?
    Using Activity Runs and Pipeline Runs tabs.

70. What are Azure Monitor and Log Analytics?
    Tools for monitoring and analyzing Azure resources.

71. How do you implement incremental data loads?
    Using watermark columns and filters.

72. What is Slowly Changing Dimension (SCD)?
    Handles historical data in dimension tables.

73. What is Delta Lake?
    A storage layer in Databricks for ACID transactions.

74. What is a data mart?
    Subset of a data warehouse, focused on a business line.

75. What is OLAP vs OLTP?

• OLAP: Analytics
• OLTP: Transactional systems

76. What is a surrogate key?
    Artificial key used as a unique identifier.

77. What is a fact table?
    Contains measurable data for analysis.

78. What is a dimension table?
    Describes dimensions related to fact tables.

79. What is normalization in databases?
    Organizing data to reduce redundancy.

80. What is denormalization?
    Combining tables for faster read performance.

81. What is JSON and how is it used in Azure?
    JavaScript Object Notation used for config and data formats.

82. How do you handle null values in ADF?
    Using conditional expressions or default values.

83. What is a data catalog?
    Metadata repository to discover and manage data assets.

84. What are pipelines in Azure Synapse?
    Data workflows similar to ADF pipelines.

85. What is an activity run?
    Execution instance of a pipeline activity.

86. What is a control activity in ADF?

• ForEach
• If Condition
• Execute Pipeline

87. What is concurrency in ADF pipelines?
    Number of parallel executions allowed.

88. What is a variable in ADF?
    Used to store values during pipeline execution.

89. What is a parameter in ADF?
    Used to make components dynamic and reusable.

90. What is the use of logging in ADF?
    Tracking execution and debugging.

91. How to handle large datasets in Databricks?
    Partitioning, caching, and cluster tuning.

92. What is a notebook in Databricks?
    Interactive environment for running code.

93. What is a cluster in Databricks?
    Group of VMs for running workloads.

94. What is CI/CD in Azure Data Engineering?
    Automated code build, test, and deploy using tools like Azure DevOps.

95. What is Git integration in ADF?
    Version control using GitHub or Azure Repos.

96. What is dynamic content in ADF?
    Expressions used to build values at runtime.

97. What is Azure Purview?
    A unified data governance solution.

98. What is data retention?
    Policy for how long data is stored.

99. What is Azure Event Hub?
    Real-time data ingestion service.

100. What are some certifications for Azure Data Engineers?

• DP-203: Azure Data Engineer Associate
• DP-900: Azure Fundamentals