Tiger Analytics Senior Software Engineer Interview Questions and Answers

2sql 2 python questions were to be coded

Q1. Simple questions regarding bde aws were asked
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Q1. What is the difference between List and Tuple?
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Q2. What is __init__ ? Follow up question why is __ (double underscore) used?
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Q3. A SQL query based on group by and order by DESC LIMIT 1 in order to fetch highest row of a group in a dataset given by panelist.
Ans. 
Use SQL GROUP BY and ORDER BY DESC to fetch the highest row of each group in a dataset.
• Use GROUP BY to aggregate data based on a specific column.

• Use ORDER BY DESC to sort the results in descending order.

• Use LIMIT 1 to fetch only the top result from each group.

• Example: SELECT department, MAX(salary) FROM employees GROUP BY department ORDER BY MAX(salary) DESC LIMIT 1;

• This query retrieves the department with the highest ...read more
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Q4. A simple query on SQL using group by and aggregate function.
Ans. 
Using SQL's GROUP BY and aggregate functions to summarize data effectively.
• GROUP BY is used to arrange identical data into groups.

• Aggregate functions like COUNT(), SUM(), AVG(), MAX(), and MIN() summarize data.

• Example: SELECT department, COUNT(*) FROM employees GROUP BY department; returns the number of employees in each department.

• You can combine multiple aggregate functions: SELECT department, AVG(salary), MAX(salary...read more
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Q5. Panelist asked about my previous work experience and projects I worked upon earlier and the technologies used.
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Q6. Question on how do we create table using SQL Alchemy in Flask (since I had used Python Flask in one of my previous projects and had highlighted it pretty well on my resume).
Ans. 
Creating tables in Flask using SQLAlchemy involves defining models and initializing the database.
• Import necessary modules: from flask import Flask, from flask_sqlalchemy import SQLAlchemy.

• Initialize Flask app and SQLAlchemy: app = Flask(__name__), db = SQLAlchemy(app).

• Define a model class: class User(db.Model):, with attributes like id, name, email.

• Use db.create_all() to create tables based on defined models.

• Example mo...read more
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Q7. How is memory managed in Python?
Ans. 
Python uses automatic memory management through garbage collection.
• Python uses reference counting to keep track of memory usage.

• When an object's reference count drops to zero, it is deleted.

• Python also uses a garbage collector to handle circular references.

• Memory allocation is handled by the Python memory manager.

• Python provides tools like the 'gc' module for managing memory usage.
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Q1. Question on List operation.
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Q2. Do you know numpy pandas?
Ans. 
Yes, numpy and pandas are Python libraries used for data analysis and manipulation.
• NumPy is used for numerical operations on arrays and matrices.

• Pandas is used for data manipulation and analysis, providing data structures like DataFrame.

• Both libraries are commonly used in data science and machine learning.

• Example: import numpy as np; import pandas as pd;
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Q3. A question to count number of times a letter occurs in a sentence and then also find the maximum occurring letter.
Ans. 
Count letter occurrences in a sentence and identify the maximum occurring letter.
• Use a dictionary to store letter counts. Example: 'a': 3, 'b': 2.

• Iterate through each character in the sentence, ignoring spaces and punctuation.

• Find the maximum count and corresponding letter using the dictionary.

• Consider case sensitivity: 'A' and 'a' can be counted separately or together.
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Q4. Difference between generator and iterator?
Ans. 
Generator generates values on the fly while iterator iterates over a collection of values.
• Generator is a function that returns an iterator.

• Generators use 'yield' keyword to return values one at a time.

• Iterators are objects that implement the 'next' method to return the next value in a collection.

• Iterators can be created from arrays, strings, maps, sets, etc.

• Generators are useful for generating large sequences of values...read more
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Q5. What is the selling point about you why should we consider you over other candidate?
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Q1. Why are you looking for a change?
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Q2. What are your salary expectations?
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There were 4 sections-
1.Big data-some multiple choice questions
2.Python-2 basic programming questions
3.SQL-4 case questions on SQL queries
4.Pyspark-Basic multiple choice questions

Same as round 1 but there were no multiple choice questions,it was a subjective paper where they check your thought process and your approach.

Q1. Technical interview was based on -Your project discussion -Big data terminologies,Spark framework,working and architecture -Some case study questions and how you could have optimized it. -SQL basic querie...read more
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Q1. Share details of your previous job.
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Q2. Why are you looking for a change?
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Q3. What are your salary expectations?
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Q4. Tell me about yourself.
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