Top 100 Azure Data Engineer Interview Questions

Level 1

Q1. What are the practical uses of Azure Cloud?

• Cloud Storage
• App Storage
• Virtualizations
• Cloud Computing
• All Above

Q2. What is the difference between Azure Cloud Services and Azure Cloud Resources?

Q3. What are the different types of environment in Azure cloud?

• PaaS
• IaaS
• SaaS

Q4. What are the Pricing Tiers in Azure?

• Pay per month
• Pay per hour 
• Pay per GB / TB

Q5. What kind of data you can store in Azure cloud?

• File 
• Tables 
• Apps 

Q6. How do you store Files in Azure Cloud?

• Storage Account
• Data Lake Storage Account 

Q7. How do you store Tables in Azure Cloud?

• Azure Tables in Storage Account
• Data Lake Storage Account 
• Azure SQL Databases 

Q8. What kind of databases you can store in Azure Cloud?

• OLTP 
• DWH 
• OLAP 
• NoSQL Databases 

Q9. How do you generate bacpac & dacpac files in Azure Cloud?

• Bacpac File (DB Migrations): Generated from SSMS Tool: Right Click Database > Tasks > Export data Tier. This generates bacpac file. Used in DB Migrations.
• Dacpac File (DevOps @ CI-CD Pipelines): Generated from SSMS Tool: Right Click Database > Tasks > Extract data Tier. This generates dacpac file. Used in DevOps @ CI-CD Pipelines.

Q10. How do you generate dacpac files in Azure Cloud?

• Not Possible. Only possible from standalone tools like SSMS, Visual Studio, etc.. 

Q11. What are the various tools you are aware of in Azure Cloud?

• SSMS Tool
• Azure Storage Explorer 
• Azure Self Hosted IR 
• Data Migration Assistant (DMA) 
• ADS Tool 

Q12. What are the practical uses of a pipeline?

• ETL Pipelines: Used for ETL & DWH Operations.
• DevOps Pipelines: Used for Code Automations and CI-CD.

Q13. What is a Trigger in ETL process?

• Trigger is a means of execution of a published pipeline.
• Debugging is a means of testing / execution of an unpublished pipeline.

Q14. What is a linked service?

• A connection item stored in Azure Data Factory resource and Synapse Analytics resource.
• It is used to perform ETL Operations.

Q15. What is SHIR (Self-Hosted IR)?

• This IR is used to establish connections from On-Premises to Cloud. 

Q 16: What are the different ADF Copy Methods?

1. Bulk Insert 
2. Upsert 
3. Copy Command 

Q17: What is Upsert Copy Method?

• Upsert is Responsible for Data Delta Computations. 
• It is used to perform Table to Table Merge (OLTP Versus DWH).
• It Needs a Business Key [Only one business key].

Q18: What are the various ADF Optimizations?

• Staging 
• Logging (Reliable) 
• DIU : Data Integration Unit 
• DOCP : Degree of Copy parallelism 
• Partitions 
• Distributions 
• Compressions 
• Parallel Connections 

Q19: How do you implement ADF Staging?

• We can implement staging by using Storage Account and ADLS Storage Account.
• Container service (storage service) is mandatory.Reason: Staging results in automated BLOB Files for “staging” or preloading the data into storage account for faster, efficient ETL transformations.ADLS Storage Account is preferred as compared to regular Storage Account.Optimization: Deploy the storage account in the same region in which the source data resided, if possible. This results in cost optimization as well as performance (compute) optimization

Q20. What is a Data Flow in Azure Data Factory?

A Data Flow in ADF is a visual, code-free way to design and run complex data transformations such as joins, aggregations, filters, and lookups.
Example: You can join customer and order tables, calculate totals, and load them into a Data Warehouse — all visually.

Q21. Difference between Mapping Data Flow and Wrangling Data Flow

Q22. What are Integration Runtimes (IR) in ADF?

• Integration Runtime is the compute engine for data movement.
• Azure IR – For cloud-to-cloud data movement.
• Self-hosted IR (SHIR) – For on-prem to cloud movement.
• Azure-SSIS IR – To run SSIS packages in Azure.

Q23. What is the difference between ADF Pipeline and Synapse Pipeline?

Both use the same base engine, but:
ADF Pipelines – Focus on ETL/ELT workflows.
Synapse Pipelines – Designed for data warehouse automation, integrated with Synapse SQL Pools.

Q24. What are the ADF Monitoring options?

Monitor tab in ADF Studio.
Azure Monitor logs and metrics.
Email/Logic App alerts for pipeline failure or delay.

Q25. What is an Activity in ADF?

An activity defines a single step in a pipeline.
Examples: Copy activity, Lookup, Execute Stored Procedure, Data Flow, etc.

Q26. What is Delta Lake in Databricks?

Delta Lake is a storage layer providing ACID transactions, version control, and time travel for big data files.
It turns Data Lakes into reliable Data Warehouses.

Q27. What is Azure Event Hub and IoT Hub used for?

Event Hub: For streaming large amounts of telemetry data (e.g., logs, events).
IoT Hub: Specifically designed for IoT devices’ data ingestion.

Q28. What is Azure Data Explorer (ADX)?

ADX is a fast, scalable data exploration service optimized for log and telemetry analytics, using the Kusto Query Language (KQL).

Q29. What is Azure Purview (now Microsoft Purview)?

It’s a data catalogue and governance tool that helps track data lineage, classification, and compliance across Azure and on-premises data.

Q30. What are some best practices for ADF pipelines?

Parameterize linked services and datasets.
Use staging for large data loads.
Enable logging for error tracking.
Implement retry logic.
Use Data Flows for transformations instead of script-heavy logic.

Q31. How do you perform Incremental Load in ADF?

Use a watermark column like Last Modified Date to copy only new or changed records from source to destination.

Q32. What is the role of Key Vault in ADF?

Azure Key Vault securely stores credentials (like passwords, keys, tokens).
ADF can connect directly to Key Vault for secret management in linked services.

Q33. Explain an end-to-end Azure Data Engineering pipeline.

Data ingestion from on-prem SQL → ADF (Copy activity).
Storage in ADLS Gen2.
Transformation using Databricks (PySpark).
Load into Synapse dedicated pool.
Visualization in Power BI.
Monitoring with Azure Monitor and Purview governance.

Q34. What is Data Integration in Azure?

Data Integration combines data from multiple sources into a unified view.
In Azure, this is done using Azure Data Factory, Synapse Pipelines, or Databricks, integrating on-premises, cloud, and SaaS data sources.

Q35. What are Linked Services and Datasets in ADF?

Linked Service: Defines the connection to a data source (like SQL Server, ADLS).Dataset: Represents a data structure within that source (like a table or file).

Q36. What is Data Lineage and why is it important?

Data Lineage tracks data flow from source to destination.
Azure Purview provides lineage visualization for better traceability, auditing, and governance.

Q37. What is a Pipeline Parameter in ADF?

A variable passed to a pipeline to make it dynamic and reusable.
Example: Source and destination file names can be parameterized.

Q38. How do you optimize data transformations in Databricks?

Use Delta Lake format instead of CSV/Parquet.
Enable Adaptive Query Execution (AQE).
Cache frequently used data frames.
Repartition large datasets.

Q39. What is a Tumbling Window Trigger in ADF?

It executes pipelines in fixed, non-overlapping time intervals, useful for processing data in time slices (e.g., every 15 minutes).

Q40. What is a Stored Procedure Activity in ADF?

This activity runs stored procedures in Azure SQL or Synapse as part of a pipeline, typically used for data validation or aggregation post-load.

Q41. What are Synapse Workspaces?

A unified environment to manage SQL Pools, Spark Pools, Pipelines, and Data Explorer under one interface.

Q42. How do you secure data pipelines in Azure?

Use Managed Identity.
Store secrets in Key Vault.
Implement RBAC for ADF and Storage Accounts.
Enable private endpoints.

Q43. What are Integration Datasets in ADF?

Datasets used to connect activities together, often serving as input/output between multiple steps in a pipeline.

Q44. What is Data Drift?

Data drift is unexpected change in source data structure or semantics over time.
ADF’s Data Flow schema drift setting helps handle such changes dynamically.

Q45. What is a Data Flow in Azure Data Factory?

A Data Flow in ADF is a visual, code-free way to design and run complex data transformations such as joins, aggregations, filters, and lookups.
Example: You can join customer and order tables, calculate totals, and load them into a Data Warehouse — all visually.

Q46. Difference between Mapping Data Flow and Wrangling Data Flow

Q47.What are Integration Runtimes (IR) in ADF?

Integration Runtime is the compute engine for data movement.

Azure IR – For cloud-to-cloud data movement.

Self-hosted IR (SHIR) – For on-prem to cloud movement.

Azure-SSIS IR – To run SSIS packages in Azure.

Q48.What is the difference between ADF Pipeline and Synapse Pipeline?

Both use the same base engine, but:

ADF Pipelines – Focus on ETL/ELT workflows.

Synapse Pipelines – Designed for data warehouse automation, integrated with Synapse SQL Pools.

Q49.What are the ADF Monitoring options?

• Monitor tab in ADF Studio.
• Azure Monitor logs and metrics.
• Email/Logic App alerts for pipeline failure or delay.

Q50. What is an Activity in ADF?

An activity defines a single step in a pipeline.
Examples: Copy activity, Lookup, Execute Stored Procedure, Data Flow, etc