Real interview questions asked at Virtusa. Practice the most frequently asked questions and land your next role.
Virtusa data engineering interviews test your ability across multiple domains. These questions are sourced from real Virtusa interview experiences and sorted by frequency. Practice the ones that matter most.
Explain the types of triggers in ADF, including schedule, tumbling window, and event-based triggers.
What challenges can arise when using high degrees of parallelism?
Differentiate between global and local variables in ADF.
Explain how you debug failed pipelines in ADF.
Explain the use of Web Activity in ADF.
How are Logic Apps used in ADF projects?
How can you increase parallelism in ADF pipelines?
How do Logic Apps enhance notification workflows for monitoring pipelines?
How do you delete files older than 30 days using ADF?
How do you handle API rate limits in ADF?
How do you merge data from different sources in ADF while maintaining data quality?
How do you use Azure Databricks notebooks within ADF pipelines?
How would you migrate 1TB of data using ADF?
What are common issues faced with REST APIs in ADF, and how do you resolve them?
What are the limitations of using Azure Hybrid Connections?
What are the performance considerations when integrating Logic Apps with ADF?
How do you handle schema mismatches during merging?
How do you manage authentication for REST API calls using Web Activity?
How do you secure the connection for sensitive data transfers?
What are the key logs or metrics you analyze first?
What are the limitations of Assert Transformations in complex data flows?
What scenarios require local variables instead of global ones?
What steps do you take to debug authentication errors in REST API calls?
What strategies do you use to handle network bottlenecks?
What would you do if the files are stored in multiple folders with varying retention policies?
Can you chain multiple triggers for a single pipeline?
Can you provide a use case where Assert Transformations helped maintain data quality?
How do partitioning strategies differ between source and sink?
How do tumbling window triggers ensure data consistency in batch processing?
How do you integrate with an on-premises SQL Server without using SHIR?
What are Assert Transformations, and where are they used?
How can lifecycle management policies complement ADF for this task?
How does Data Flow optimize data transformations for large datasets?
What configurations are needed to pass parameters to a Databricks notebook?
What techniques ensure deduplication in large datasets?
How do you ensure fault tolerance during large-scale data migrations?
How do you pass global variables between pipelines?
How do you use dependency tracing to identify root causes in pipeline failures?
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