HCL Group Data Engineer Interview Questions and Answers

Q1. Scenario based questions on Azure data factory and pipelines
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Q2. Optimisation technic to improve the performance of databricks
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Q3. What is Autoloader
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Q4. What is unity catalog
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Q5. How you do the alerting mechanism in adf for failed pipelines
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Q1. What are different type of joins available in Databricks?
Ans. 
Different types of joins available in Databricks include inner join, outer join, left join, right join, and cross join.
• Inner join: Returns only the rows that have matching values in both tables.

• Outer join: Returns all rows when there is a match in either table.

• Left join: Returns all rows from the left table and the matched rows from the right table.

• Right join: Returns all rows from the right table and the matched rows ...read more
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Q2. How do you make your data pipeline fault tolerant?
Ans. 
Implementing fault tolerance in a data pipeline involves redundancy, monitoring, and error handling.
• Use redundant components to ensure continuous data flow

• Implement monitoring tools to detect failures and bottlenecks

• Set up automated alerts for immediate response to issues

• Design error handling mechanisms to gracefully handle failures

• Use checkpoints and retries to ensure data integrity
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Q3. What is AutoLoader?
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AutoLoader is a feature in data engineering that automatically loads data from various sources into a data warehouse or database.
• Automates the process of loading data from different sources

• Reduces manual effort and human error

• Can be scheduled to run at specific intervals

• Examples: Apache Nifi, AWS Glue
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Q1. How do you connect to different services in Azure?
Ans. 
To connect to different services in Azure, you can use Azure SDKs, REST APIs, Azure Portal, Azure CLI, and Azure PowerShell.
• Use Azure SDKs for programming languages like Python, Java, C#, etc.

• Utilize REST APIs to interact with Azure services programmatically.

• Access and manage services through the Azure Portal.

• Leverage Azure CLI for command-line interface interactions.

• Automate tasks using Azure PowerShell scripts.
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Q2. What are linked Services?
Ans. 
Linked Services are connections to external data sources or destinations in Azure Data Factory.
• Linked Services define the connection information needed to connect to external data sources or destinations.

• They can be used in Data Factory pipelines to read from or write to external systems.

• Examples of Linked Services include Azure Blob Storage, Azure SQL Database, and Amazon S3.
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Q1. Sql commands group by and order by
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Q1. Cicd pipeline and kafka
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Q1. Reparitition and pipelines
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Q1. Joins operations
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Q1. Explain adf questions in detail
Ans. 
ADF questions refer to Azure Data Factory questions which are related to data integration and data transformation processes.
• ADF questions are related to Azure Data Factory, a cloud-based data integration service.

• These questions may involve data pipelines, data flows, activities, triggers, and data movement.

• Candidates may be asked about their experience with designing, monitoring, and managing data pipelines in ADF.

• Exam...read more
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Q2. Project related questions
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Q1. Project data related questions
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Q2. Databricks and SQL interview questions
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Q1. What are the optimization techniques used in Apache Spark?
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Q2. 2 SQL queries , 1 PySpark code and 1 Python Code .
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Q3. 2-3 Scenario Based questions from ADF and databricks .
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Q1. Difference between rank and dense_rank, Left vs Left anti join
Ans. 
Rank assigns unique ranks to rows, while dense_rank handles ties by assigning the same rank to tied rows. Left join includes all rows from the left table and matching rows from the right table, while left anti join includes only rows from the left table that do not have a match in the right table.
• Rank assigns unique ranks to rows based on the specified order, while dense_rank handles ties by assigning the same rank to ...read more
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Q2. Python list comprehension, SQL query
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Q1. Project related questions
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Aptitude test involved with quantative aptitude, logical reasoning and reading comprehensions.

Q1. Tell me your introduction.
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Q2. Tell me about your skills.
Ans. 
I have strong skills in data processing, ETL, data modeling, and programming languages like Python and SQL.
• Proficient in data processing and ETL techniques

• Strong knowledge of data modeling and database design

• Experience with programming languages like Python and SQL

• Familiarity with big data technologies such as Hadoop and Spark
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Q1. Are you ready relocate,?
Ans. 
Yes, I am open to relocating for the right opportunity.
• I am willing to relocate for the right job opportunity.

• I have experience moving for previous roles.

• I am flexible and adaptable to new locations.

• I am excited about the possibility of exploring a new city or country.
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Q2. Document verification
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Q1. About python, sql, pyspark
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Q2. Spark Architecture.
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Q1. When can you join.
Ans. 
I can join within two weeks of receiving an offer.
• I can start within two weeks of receiving an offer.

• I need to give notice at my current job before starting.

• I have some personal commitments that I need to wrap up before joining.
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Q2. .
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