Top 10 Cognizant Azure Data Factory & Azure Databricks Interview Questions (2026)
Prepare for Cognizant Azure Data Engineer interviews with the most frequently asked Azure Data Factory, Azure Databricks, ADLS Gen2, Delta Lake, PySpark, SQL and ETL interview questions.
Top 8 Cognizant Azure Data Engineer Interview Questions
Cognizant Azure Data Engineer interviews commonly focus on Azure Data Factory, Azure Databricks, PySpark, ADLS Gen2, Azure SQL Database, Azure DevOps, and real-world ETL implementation scenarios. Candidates should be comfortable explaining production use cases and optimization techniques.
1. What is the difference between repartition() and coalesce() in PySpark?
Both repartition() and coalesce() are used to change the number of partitions in a DataFrame. repartition() performs a full shuffle and can both increase or decrease partitions, while coalesce() only decreases partitions without a full shuffle, making it more efficient when reducing partitions.
repartition(n)
ā¢ Can increase or decrease partitions
ā¢ Performs full shuffle
ā¢ Better data distribution
ā¢ Higher execution cost
coalesce(n)
ā¢ Only decreases partitions
ā¢ Avoids full shuffle
ā¢ Faster execution
ā¢ Commonly used before writing output files2. How do you cache and persist data in PySpark?
cache() stores a DataFrame in memory for faster access during repeated operations. persist() allows selecting different storage levels such as memory, disk, or both. After processing, unpersist() should be called to release cached resources.
from pyspark.storagelevel import StorageLevel
# Store in memory
df.cache()
# Store in memory and disk
df.persist(StorageLevel.MEMORY_AND_DISK)
# Remove cached data
df.unpersist()3. How do you use Azure Logic Apps to automate SQL database workflows?
Azure Logic Apps is a serverless workflow service that automates SQL database operations using built-in connectors. A workflow can be triggered by a schedule or HTTP request, execute SQL queries or stored procedures, and then send notifications or update downstream applications like Power BI or Microsoft Teams.
Schedule Trigger
ā
ā¼
Run SQL Query /
Stored Procedure
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ā¼
Send Email
or Update Power BI
ā
ā¼
Workflow Completed4. What is the difference between ADLS Gen1 and ADLS Gen2?
ADLS Gen2 is the modern version of Azure Data Lake Storage built on Azure Blob Storage. It offers lower storage costs, better performance, hierarchical namespace support, Azure RBAC integration, and seamless integration with Azure analytics services compared to ADLS Gen1.
ADLS Gen1
-----------
ā¢ Based on HDFS
ā¢ Higher Cost
ā¢ ACL Security
ā¢ Limited Azure Integration
ADLS Gen2
-----------
ā¢ Built on Azure Blob Storage
ā¢ Lower Cost
ā¢ ACL + RBAC
ā¢ Better Performance
ā¢ Hierarchical Namespace
ā¢ Recommended for Modern Data Lakes5. Write a SQL query to find gaps in a sequence of numbers.
The following query identifies missing numbers in a sequence by performing a self join on consecutive values.
SELECT curr.id + 1 AS missing_id
FROM your_table curr
LEFT JOIN your_table next
ON curr.id + 1 = next.id
WHERE next.id IS NULL;6. How do you ensure high availability and disaster recovery for Azure SQL Database?
High availability is achieved using Premium or Business Critical service tiers with zone redundancy and Auto-Failover Groups. Disaster recovery is implemented through Active Geo-Replication, Point-in-Time Restore, automated backups, and Long-Term Backup Retention policies.
7. Explain the role of Azure DevOps Pipelines.
Azure DevOps Pipelines automate Continuous Integration (CI) and Continuous Deployment (CD). They build, test, validate, and deploy applications, Azure Data Factory pipelines, Databricks notebooks, SQL scripts, and other Azure resources using YAML or Classic pipelines.
Developer
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ā¼
Git Repository
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ā¼
CI Pipeline
(Build & Test)
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ā¼
CD Pipeline
(Deploy)
ā
ā¼
ADF / Databricks / Azure SQL8. How do you implement data masking in Azure Data Factory?
Sensitive data can be masked using Derived Column transformations in Mapping Data Flows. Azure SQL Dynamic Data Masking, Azure Key Vault for secret management, and row-level or column-level security can also be used to protect confidential information in enterprise data pipelines.
Data Source
ā
ā¼
ADF Mapping Data Flow
ā
Derived Column
(Mask Sensitive Data)
ā
ā¼
Azure SQL / ADLS Gen2
ā
ā¼
Secure ReportingInterview Tip
Cognizant interviewers usually expect practical answers. Explain the business requirement, Azure services used, implementation approach, optimization techniques, security considerations, and the final business outcome whenever discussing real-world scenarios.