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Expleo Solutions
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I applied via Walk-in and was interviewed in Oct 2023. There were 3 interview rounds.
I applied via Naukri.com and was interviewed before May 2023. There were 2 interview rounds.
Intermediate concepts in data science include machine learning, data visualization, and statistical analysis.
Machine learning algorithms such as regression, classification, and clustering
Data visualization techniques like scatter plots, histograms, and heatmaps
Statistical analysis methods such as hypothesis testing, ANOVA, and regression analysis
Expleo Solutions interview questions for designations
I applied via Naukri.com and was interviewed before Feb 2023. There were 3 interview rounds.
The candidate is asked to write a program to find the number of appearances of a specific character in a given string.
Use a loop to iterate through each character in the string and compare it with the target character.
Keep a count of the number of times the target character appears in the string.
Return the count as the result.
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I applied via Referral and was interviewed before Jan 2021. There was 1 interview round.
posted on 28 Mar 2018
I applied via Other and was interviewed in Nov 2017. There were 5 interview rounds.
As a Senior Software Engineer, I worked with various tools and technologies to develop and maintain software applications.
Developed and maintained software applications using Java, Python, and C++ programming languages
Used Agile methodology for software development and collaborated with cross-functional teams
Worked with various tools such as Git, JIRA, Jenkins, and Docker for version control, issue tracking, continuous...
I applied via Recruitment Consultant and was interviewed in Jul 2018. There were 3 interview rounds.
The biggest challenge in developing Azure solution was managing the complexity of the cloud environment.
Managing the complexity of the cloud environment
Ensuring scalability and reliability
Integrating with existing systems
Securing the solution
Optimizing cost
Example: Migrating a legacy application to Azure
Implementing tumbling window in Azure Data Factory without using the feature
Create a pipeline with a trigger that runs at the desired interval
Use a lookup activity to retrieve the data for the current window
Use a foreach activity to iterate over the retrieved data
Perform the required operations on the data within the foreach activity
Write the output to the desired destination
My suggestion for implementation in Azure Data Factory v2 is to use the Mapping Data Flow feature.
Utilize Mapping Data Flow for complex data transformations
Take advantage of the visual interface to design and debug data flows
Leverage the built-in data integration capabilities with other Azure services
Use data flow parameters and expressions for dynamic transformations
Monitor and optimize data flow performance using dat
posted on 24 Mar 2021
Some of the top questions asked at the Expleo Solutions Senior Software Engineer interview -
based on 10 interviews
2 Interview rounds
based on 40 reviews
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