Top 10 Publicis Sapient technical interview questions for Cloud & AI

Looking for Publicis Sapient technical interview questions? Here are some scenario-based and coding questions for the Senior Associate Data Engineering (L2) - Big Data Azure role at Publicis Sapient in Bangalore:

Scenario-based questions for Azure Cloud:

1. You are designing a data engineering pipeline for a new big data application on Azure. What are some of the key considerations that you would need to keep in mind?
2. You are troubleshooting a performance issue in your big data pipeline on Azure. How would you identify the root cause of the issue and resolve it quickly and efficiently?
3. You are working on a team to develop and deploy a new machine-learning model to production on Azure. How would you implement an MLOps pipeline to ensure that the model is deployed and maintained efficiently and effectively?
4. You are responsible for managing a large-scale Azure Databricks cluster. How would you ensure that the cluster is highly available and scalable?
5. You are migrating a legacy on-premises data warehouse to Azure Synapse Analytics. How would you design and implement a migration plan?
6. You are responsible for the security of your Azure data environment. How would you implement security best practices to protect your data and applications?
7. You are working on a team to implement a new CI/CD pipeline for your Azure data environment. What are some of the key considerations that you would need to keep in mind?
8. You are responsible for monitoring and troubleshooting your Azure data environment. What are some of the tools and techniques that you would use?
9. You are responsible for managing the costs of your Azure data environment. What are some of the ways that you would optimize costs?
10. You are working on a team to implement a new data science platform on Azure. What are some of the key considerations that you would need to keep in mind?

Coding questions for Azure Cloud:

1. Write a Databricks notebook to read data from an Azure Blob Storage container, transform the data, and then write the transformed data to an Azure Synapse Analytics data warehouse.
2. Write a Python script to use the Azure Machine Learning SDK to train a machine learning model on Azure Databricks and then deploy the model to Azure Kubernetes Service.
3. Write a Terraform configuration to create an Azure Databricks cluster with a specific number of worker nodes and a specific version of the Databricks Runtime.
4. Write a PowerShell script to use the Azure Data Lake Store Tools SDK to create a new Azure Data Lake Store directory and then upload a file to the directory.
5. Write an Azure Synapse Analytics SQL script to query a data warehouse and generate a report on the top 10 products by sales.
6. Write an Azure Stream Analytics query to process data from an Azure Event Hub and then write the processed data to an Azure SQL Database table.
7. Write a Python script to use the Azure Machine Learning SDK to evaluate the performance of a machine learning model deployed to Azure Kubernetes Service.
8. Write a Terraform configuration to create an Azure Synapse Analytics workspace with a specific number of SQL Data Warehouse units and a specific amount of storage capacity.
9. Write a PowerShell script to use the Azure Data Factory SDK to create a new Azure Data Factory pipeline and then add a Databricks copy activity to the pipeline.
10. Write an Azure Synapse Analytics SQL script to merge the data from two tables into a single table.

These are just a few examples, and the specific questions that you are asked will vary depending on the specific role and project. However, by preparing for these types of questions, you will be well on your way to acing your next data engineering interview.

Keep looking for more Publicis sapient interview questions in future.