LTIMindtree Senior Data Engineer Interview Questions, Process, and Tips for Experienced

Simple coding questions on arrays and strings.

Q1. Resume go through.
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Q1. Personal and Cultural Questions
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Q1. 1) Snowflake architecture in your current project.
Ans. 
Snowflake architecture is used in our project for cloud-based data warehousing.
• Snowflake follows a multi-cluster shared data architecture.

• It separates storage and compute resources, allowing for independent scaling.

• Data is stored in virtual warehouses, which are compute clusters that can be scaled up or down based on workload.

• Snowflake uses a unique architecture called a multi-cluster, shared data architecture, which s...read more
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Q2. 2) Database roles in Snowflake.
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Database roles in Snowflake define permissions and access control for users and objects.
• Database roles in Snowflake are used to manage permissions and access control for users and objects.

• Roles can be assigned to users or other roles to grant specific privileges.

• Examples of roles in Snowflake include ACCOUNTADMIN, SYSADMIN, SECURITYADMIN, and PUBLIC.
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Q3. 3) Session Policy in Snowflake.
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Session Policy in Snowflake defines the behavior of a session, including session timeout and idle timeout settings.
• Session Policy can be set at the account, user, or role level in Snowflake.

• Session Policy settings include session timeout, idle timeout, and other session-related configurations.

• Example: Setting a session timeout of 30 minutes will automatically end the session if there is no activity for 30 minutes.
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Q4. 4) Describe the SSO process between Snowflake and Azure Active Directory.
Ans. 
SSO process between Snowflake and Azure Active Directory involves configuring SAML-based authentication.
• Configure Snowflake to use SAML authentication with Azure AD as the identity provider

• Set up a trust relationship between Snowflake and Azure AD

• Users authenticate through Azure AD and are granted access to Snowflake resources

• SSO eliminates the need for separate logins and passwords for Snowflake and Azure AD
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Q5. 5) Network Policy in Snowflake.
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Network Policy in Snowflake controls access to Snowflake resources based on IP addresses or ranges.
• Network Policies are used to restrict access to Snowflake resources based on IP addresses or ranges.

• They can be applied at the account, user, or role level.

• Network Policies can be used to whitelist specific IP addresses or ranges that are allowed to access Snowflake resources.

• They can also be used to blacklist IP addresse...read more
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Q6. 6) Automatic data loading from pipes in to Snowflake.
Ans. 
Automate data loading from pipes into Snowflake for efficient data processing.
• Use Snowpipe, a continuous data ingestion service provided by Snowflake, to automatically load data from pipes into Snowflake tables.

• Snowpipe monitors a stage for new data files and loads them into the specified table in real-time.

• Configure Snowpipe to trigger a data load whenever new data files are added to the stage, eliminating the need fo...read more
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Q7. 7) How does query acceleration speed up query processing?
Ans. 
Query acceleration speeds up query processing by optimizing query execution and reducing the time taken to retrieve data.
• Query acceleration uses techniques like indexing, partitioning, and caching to optimize query execution.

• It reduces the time taken to retrieve data by minimizing disk I/O and utilizing in-memory processing.

• Examples include using columnar storage formats like Parquet or optimizing join operations.
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Quite simple need to explain about previous projects and experience and basic questions

Q1. It is in detail about all the key skills .
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Q1. Salary details and basic work culture
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Big data and sql,python related questions

Q1. Big data and python related questions
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Q1. Previous company questions and general HR questions
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Q1. Introduction of urs
Ans. 
I am a Senior Data Engineer with expertise in data processing and analysis.
• Experienced in designing and implementing data pipelines

• Proficient in programming languages like Python and SQL

• Skilled in working with big data technologies like Hadoop and Spark

• Familiar with data warehousing and ETL processes

• Strong problem-solving and analytical skills
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Q2. Basic structured query language
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Q1. Introduction of urs
Ans. 
I am a Senior Data Engineer with expertise in data processing and analysis.
• Experienced in designing and implementing data pipelines

• Proficient in programming languages like Python and SQL

• Skilled in working with big data technologies such as Hadoop and Spark

• Familiar with data warehousing concepts and ETL processes

• Strong problem-solving and troubleshooting skills

• Effective communication and collaboration with cross-functio
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Q1. Pyspark, SQL questions
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Q1. Questions about previous project
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Q1. Salary Discussions and expectations
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