Equity Data Science Senior Data Engineer Interview Questions, Process, and Tips for Experienced

Python coding question and couple of SQL questions

Q1. Spark Optimization techniques
Ans. 
Spark optimization techniques focus on improving performance and efficiency of Spark jobs.
• Partitioning data to optimize parallelism

• Caching frequently accessed data

• Using broadcast variables for small lookup tables

• Avoiding shuffling operations whenever possible

• Tuning memory settings for optimal performance
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Q2. Current Project discussions
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Q3. Difficulties I have faced during during ETL pipelines
Ans. 
I have faced difficulties in handling large volumes of data, ensuring data quality, and managing dependencies in ETL pipelines.
• Handling large volumes of data can lead to performance issues and scalability challenges.

• Ensuring data quality involves dealing with data inconsistencies, errors, and missing values.

• Managing dependencies between different stages of the ETL process can be complex and prone to failures.
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Q1. No questions just asked to write SQL query and Python script. Not sure what they expect from it.
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Q2. Write a SQL query
Ans. 
SQL query to retrieve all employees from a table named 'employees'
• Use SELECT * FROM employees;

• Replace '*' with specific columns if needed, e.g. SELECT employee_id, name FROM employees;
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Q3. Write a Python program
Ans. 
Python program to print 'Hello, World!'
• Use the print() function in Python to display text on the screen

• Enclose the text in single or double quotes to indicate a string
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Q1. Self intro and questions based on previous experiance
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Q1. How to work with nested json using pyspark
Ans. 
Working with nested JSON using PySpark involves using the StructType and StructField classes to define the schema and then using the select function to access nested fields.
• Define the schema using StructType and StructField classes

• Use the select function to access nested fields

• Use dot notation to access nested fields, for example df.select('nested_field.sub_field')
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Q2. How to implement scd2 step by step
Ans. 
Implementing SCD2 involves tracking historical changes in data over time.
• Identify the business key that uniquely identifies each record

• Add effective start and end dates to track when the record was valid

• Insert new records with updated data and end date of '9999-12-31'

• Update end date of previous record when a change occurs
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Q1. Write a SQL query to select data from table 2 where data exists in table 1
Ans. 
Use a SQL query to select data from table 2 where data exists in table 1
• Use a JOIN statement to link the two tables based on a common column

• Specify the columns you want to select from table 2

• Use a WHERE clause to check for existence of data in table 1
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Q2. After performing joins how many records would be retrieved for inner, left, right and outer joins
Ans. 
The number of records retrieved after performing joins depends on the type of join - inner, left, right, or outer.
• Inner join retrieves only the matching records from both tables

• Left join retrieves all records from the left table and matching records from the right table

• Right join retrieves all records from the right table and matching records from the left table

• Outer join retrieves all records from both tables, filling
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Q1. About previous company and reason for leaving
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Q1. How the files will be read in AWS GLUE
Ans. 
Files can be read in AWS Glue using Data Catalog, crawlers, and Glue ETL jobs.
• Use AWS Glue Data Catalog to store metadata information about the files.

• Crawlers can automatically infer the schema of the files and populate the Data Catalog.

• Glue ETL jobs can then be used to read the files from various sources like S3, RDS, etc.

• Supports various file formats like CSV, JSON, Parquet, etc.
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Q1. How to get duplicate records
Ans. 
Duplicate records can be identified using SQL queries by comparing columns and using aggregate functions.
• Use GROUP BY clause with COUNT() function to identify duplicate records

• Use HAVING clause to filter out records with count greater than 1

• Join the table with itself on specific columns to find duplicates
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Q2. How to get the second highest salary
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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.
Ans. 
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.
Ans. 
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.
Ans. 
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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Find duplicates in a list

Q1. Rank types in SQL
Ans. 
Rank types in SQL
• RANK(): assigns a unique rank to each row within the result set

• DENSE_RANK(): assigns a unique rank to each row within the result set, but may have gaps

• ROW_NUMBER(): assigns a unique number to each row within the result set
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Q2. Row_Number in sql server
Ans. 
Row_Number is a function in SQL Server that assigns a unique sequential number to each row in a result set.
• Row_Number is used to generate a unique identifier for each row in a result set

• It is commonly used for pagination, ranking, and partitioning data

• The function requires an ORDER BY clause to determine the order of the rows

• The result of Row_Number is an integer value starting from 1
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Q3. Performance Tuning in sql
Ans. 
Performance tuning in SQL involves optimizing queries, indexes, and database configurations to improve query execution time.
• Identify and optimize slow-performing queries

• Create and maintain appropriate indexes

• Partition large tables to improve query performance

• Optimize database configurations and server settings

• Use query execution plans to identify bottlenecks

• Consider denormalization for frequently accessed data

• Use appro...read more
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