Complete Preparation Guide for USA Jobs

Target Roles

Python Developer
Software Engineer
Senior Software Engineer
AWS Data Engineer
Cloud Engineer
Solutions Architect
Machine Learning Engineer
AI Engineer
MLOps Engineer
Data Engineer
Staff Engineer
Principal Engineer

Module 1: Python Fundamentals (40 Questions)

Module 2: Data Structures (30 Questions)

Module 3: OOP Concepts (35 Questions)

Module 4: Functions & Functional Programming (20 Questions)

Module 5: Exception Handling (15 Questions)

Module 6: File Handling (15 Questions)

Module 7: Iterators & Generators (20 Questions)

Module 8: Decorators & Context Managers (20 Questions)

Module 9: Multithreading & Multiprocessing (25 Questions)

Module 10: Async Programming (20 Questions)

Module 11: Memory Management & Internals (25 Questions)

Module 12: Advanced Python (30 Questions)

Module 13: Database Programming (15 Questions)

Module 14: API Development (20 Questions)

Module 15: Pandas & NumPy (30 Questions)

Module 16: AWS + Python (40 Questions)

Module 17: Data Engineering with Python (35 Questions)

Module 18: Machine Learning & AI Python (25 Questions)

Module 19: System Design using Python (25 Questions)

Module 20: Coding Challenges (50 Questions)

Total Questions: 500+

MODULE 1: PYTHON FUNDAMENTALS

Q1. What is Python?

Python is a high-level, interpreted, object-oriented programming language developed by Guido van Rossum in 1991.

Features:

Easy syntax
Dynamically typed
Interpreted
Open source
Cross-platform

Example:

print("Hello World")

Q2. Why is Python popular?

Answer:

Simplicity
Large ecosystem
AI/ML support
Cloud automation
Data Engineering
Web development

Q3. Explain Python execution flow.

Flow:

Source Code
↓
Byte Code (.pyc)
↓
Python Virtual Machine
↓
Execution

Interview Tip:
Senior interviews frequently ask this.

Q4. What is Dynamic Typing?

Python determines variable type at runtime.

x = 10
x = "Hello"

No explicit declaration required.

Q5. What are Python keywords?

Examples:

if
else
for
while
try
except
class
def
yield
async
await

Q6. Difference between Python 2 and Python 3?

Feature	Python 2	Python 3
Print	Statement	Function
Unicode	Limited	Full Support
Division	Integer	Float
Support	Ended	Active

Q7. What is PEP 8?

Python coding standard.

Example:

def calculate_salary():
    pass

Best Practices:

4 spaces indentation
Meaningful variable names
Maximum 79 characters per line

Q8. What are mutable objects?

Can be modified after creation.

Examples:

list
dict
set

Q9. What are immutable objects?

Cannot change after creation.

Examples:

str
tuple
int
float

Q10. Explain Python namespaces.

Types:

Local
Global
Built-in
Enclosing

LEGB Rule:

Local
Enclosing
Global
Built-in

MODULE 2: DATA STRUCTURES

Q11. Difference between List and Tuple

Feature	List	Tuple
Mutable	Yes	No
Speed	Slower	Faster
Memory	More	Less

Example:

lst = [1,2,3]
tpl = (1,2,3)

Q12. When should you use tuples?

Use tuples when:

Data should not change
Configuration storage
Database records
Dictionary keys

Q13. What is a Dictionary?

Key-value storage.

employee = {
 "name":"John",
 "salary":50000
}

Complexity:

Lookup O(1)
Insert O(1)
Delete O(1)

Q14. How does dictionary work internally?

Uses Hash Tables.

Steps:

Key hashed
Bucket identified
Value stored

Q15. What is Hash Collision?

Multiple keys generate same hash value.

Resolved using:

Open Addressing
Chaining

Q16. What is Set?

Unordered collection of unique elements.

s = {1,2,3}

Use cases:

Duplicate removal
Membership testing

Q17. List Comprehension vs Loop

Traditional:

squares = []

for i in range(10):
    squares.append(i*i)

Comprehension:

squares = [i*i for i in range(10)]

Q18. Time Complexity of List Operations

Operation	Complexity
Access	O(1)
Append	O(1)
Insert	O(n)
Delete	O(n)

Q19. Difference between append() and extend()?

append():

a.append([4,5])

extend():

a.extend([4,5])

extend adds individual elements.

Q20. Explain slicing.

nums = [1,2,3,4,5]

nums[1:4]

Output:

[2,3,4]

MODULE 3: OBJECT ORIENTED PROGRAMMING

Q21. What is OOP?

Programming based on objects.

Four Pillars:

Encapsulation
Inheritance
Polymorphism
Abstraction

Q22. What is a Class?

Blueprint for objects.

class Employee:
    pass

Q23. What is an Object?

Instance of a class.

emp = Employee()

Q24. What is Constructor?

Automatically invoked during object creation.

class Employee:

    def __init__(self,name):
        self.name = name

Q25. What is Encapsulation?

Hides internal state.

class Account:

    def __init__(self):
        self.__balance = 1000

Benefits:

Security
Maintainability

Q26. What is Inheritance?

Allows code reuse.

class Animal:
    pass

class Dog(Animal):
    pass

Q27. Types of Inheritance?

Single
Multiple
Multilevel
Hierarchical
Hybrid

Q28. What is Method Overriding?

Child class modifies parent behavior.

class Animal:
    def sound(self):
        pass

class Dog(Animal):
    def sound(self):
        print("Bark")

Q29. What is Polymorphism?

Same interface, multiple implementations.

Example:

obj.sound()

Works for Dog, Cat, Cow.

Q30. What is Abstraction?

Hide implementation details.

from abc import ABC

MODULE 4: FUNCTIONS

Q31. What are *args?

Accept variable positional arguments.

def add(*args):
    return sum(args)

Q32. What are **kwargs?

Accept variable keyword arguments.

def display(**kwargs):
    print(kwargs)

Q33. What is Lambda?

Anonymous function.

square = lambda x:x*x

Q34. What is map()?

Transforms elements.

map(lambda x:x*2, nums)

Q35. What is filter()?

Filters elements.

filter(lambda x:x>5, nums)

MODULE 5: EXCEPTION HANDLING

Q36. What is Exception?

Runtime error.

Examples:

ValueError
TypeError
IndexError
KeyError

Q37. Exception Handling Syntax

try:
    risky()

except Exception as e:
    print(e)

finally:
    cleanup()

Q38. Difference between Exception and Error?

Exception:

Recoverable

Error:

Serious system issue

Q39. What is Finally?

Always executes.

Used for:

Closing files
Releasing connections

Q40. How to create custom exception?

class SalaryException(Exception):
    pass

MODULE 6–20 (ADVANCED/SENIOR LEVEL)

Below are the remaining high-priority questions grouped by topic. In a real interview, these are asked more frequently than basic syntax.

GENERATORS & ITERATORS

What is an iterator?
What is a generator?
yield vs return?
Why are generators memory efficient?
Generator expression vs list comprehension?
Infinite generators?
Itertools library?
Custom iterator implementation?
next() function?
StopIteration exception?

DECORATORS

What is a decorator?
Why use decorators?
Logging decorator?
Authentication decorator?
Timing decorator?
Nested decorators?
Class decorators?
functools.wraps?
Parameterized decorators?
Production use cases?

CONTEXT MANAGERS

What is context manager?
enter and exit?
with statement?
Database connection management?
Custom context manager?

THREADING & MULTIPROCESSING

What is a thread?
What is a process?
What is GIL?
Why does GIL exist?
Threading vs Multiprocessing?
ThreadPoolExecutor?
ProcessPoolExecutor?
Race conditions?
Locks?
Semaphores?
Deadlocks?
Queues?
Producer Consumer pattern?
Concurrent Futures?
Real-world AWS use cases?

ASYNCIO

What is async programming?
async vs threading?
async vs multiprocessing?
Event loop?
Coroutines?
await keyword?
asyncio.gather()?
Task scheduling?
aiohttp?
High-performance APIs?

MEMORY MANAGEMENT

Reference counting?
Garbage collection?
Circular references?
Memory leaks?
Weak references?
Object pooling?
Interning?
Deep copy vs shallow copy?
Memory profiler?
Optimizing large ETL jobs?

PYTHON INTERNALS

How import works?
name?
dict?
slots?
str vs repr?
MRO?
Metaclasses?
Duck typing?
Monkey patching?
Descriptors?

DATABASES

Python and MySQL?
Python and PostgreSQL?
Connection pooling?
SQL injection prevention?
ORM vs raw SQL?
SQLAlchemy?
Transactions?
ACID properties?
Bulk inserts?
Database optimization?

FASTAPI / FLASK

What is FastAPI?
Why FastAPI is popular?
Dependency Injection?
Pydantic?
REST API design?
JWT authentication?
API versioning?
Middleware?
Rate limiting?
OpenAPI?

NUMPY

131–150.

Arrays
Broadcasting
Vectorization
Memory optimization
Matrix operations
Linear algebra
Random module
NumPy internals
Performance tuning

PANDAS

151–180.

DataFrame
Series
Merge
Join
Concat
GroupBy
Window Functions
Missing values
Pivot tables
Performance tuning

AWS + PYTHON (MOST IMPORTANT FOR USA JOBS)

What is Boto3?
Upload file to S3?
Download from S3?
Read DynamoDB?
Write DynamoDB?
Invoke Lambda?
Start Glue Job?
Read Secrets Manager?
KMS Encryption?
Assume IAM Role?
Cross-account access?
SQS integration?
SNS integration?
Step Functions?
EventBridge?
Athena automation?
Redshift integration?
Bedrock API integration?
SageMaker automation?
CloudFormation automation?

DATA ENGINEERING

Build ETL in Python?
Process 1 TB file?
Chunk processing?
Streaming ETL?
PySpark integration?
Dask?
Airflow DAGs?
Data validation?
Schema evolution?
Data quality checks?
CDC processing?
Kafka consumers?
Kafka producers?
Batch vs Streaming?
Delta Lake?

MACHINE LEARNING

NumPy importance?
Pandas role?
Feature engineering?
Scikit-learn?
Model serialization?
Pickle issues?
ML pipelines?
Hyperparameter tuning?
Feature stores?
Model serving?

GENERATIVE AI

What is RAG?
Vector database?
Chunking strategies?
Embeddings?
Amazon Bedrock?
LangChain?
LlamaIndex?
Prompt engineering?
Hallucination?
Agentic AI?

SYSTEM DESIGN (SENIOR)

Design URL Shortener
Design Netflix
Design Uber
Design ChatGPT
Design Data Lake
Design ETL Framework
Design Log Processing Platform
Design Notification System
Design Real-Time Analytics
Design AI Platform

PRINCIPAL ENGINEER LEVEL

How would you redesign a Python monolith?
Scaling Python to millions of requests?
Python microservices architecture?
Multi-region deployment?
Event-driven architecture?
High availability?
Fault tolerance?
Distributed locking?
Caching strategy?
API Gateway design?
Service Mesh?
Observability?
OpenTelemetry?
Cost optimization?
Reliability engineering?

AMAZON / FAANG PYTHON QUESTIONS

Mutable default argument issue?
is vs ==?
Deep copy issue?
Decorator internals?
Generator internals?
Context manager internals?
Async internals?
Metaclass use cases?
MRO diamond problem?
Python optimization techniques?

CODING QUESTIONS (COMMON)

Reverse string
Palindrome
Fibonacci
Factorial
Anagram
Find duplicates
LRU Cache
Linked List
Binary Search
DFS
BFS
Tree Traversal
Graph Traversal
Dijkstra
Merge Intervals
Top K Elements
Sliding Window
Two Sum
Longest Substring
Kth Largest Element

SENIOR CODING

Rate Limiter
Distributed Cache
Thread-safe Queue
Async Web Crawler
ETL Framework
Retry Framework
Circuit Breaker
Pub/Sub System
Job Scheduler
Mini API Gateway

U.S. Interview Focus Areas (Highest Priority)

If you are targeting:

AWS Data Engineer
AI Engineer
Cloud Engineer
Solutions Architect
Senior Python Engineer

Focus heavily on:

OOP
Generators
Decorators
Context Managers
Threading vs Multiprocessing
Asyncio
Memory Management
Pandas
NumPy
Boto3
FastAPI
ETL Design
PySpark
Airflow
RAG
Amazon Bedrock
System Design
Distributed Systems
API Design
Python Internals

These 20 areas account for the majority of Python questions asked in mid-level to principal-level interviews across companies such as Amazon, Microsoft, Google, Meta, and large U.S. enterprises.

Complete Preparation Guide for USA Jobs

Target Roles

TABLE OF CONTENTS

Module 1: Python Fundamentals (40 Questions)

Module 2: Data Structures (30 Questions)

Module 3: OOP Concepts (35 Questions)

Module 4: Functions & Functional Programming (20 Questions)

Module 5: Exception Handling (15 Questions)

Module 6: File Handling (15 Questions)

Module 7: Iterators & Generators (20 Questions)

Module 8: Decorators & Context Managers (20 Questions)

Module 9: Multithreading & Multiprocessing (25 Questions)

Module 10: Async Programming (20 Questions)

Module 11: Memory Management & Internals (25 Questions)

Module 12: Advanced Python (30 Questions)

Module 13: Database Programming (15 Questions)

Module 14: API Development (20 Questions)

Module 15: Pandas & NumPy (30 Questions)

Module 16: AWS + Python (40 Questions)

Module 17: Data Engineering with Python (35 Questions)

Module 18: Machine Learning & AI Python (25 Questions)

Module 19: System Design using Python (25 Questions)

Module 20: Coding Challenges (50 Questions)

MODULE 1: PYTHON FUNDAMENTALS

Q1. What is Python?

Q2. Why is Python popular?

Q3. Explain Python execution flow.

Q4. What is Dynamic Typing?

Q5. What are Python keywords?

Q6. Difference between Python 2 and Python 3?

Q7. What is PEP 8?

Q8. What are mutable objects?

Q9. What are immutable objects?

Q10. Explain Python namespaces.

MODULE 2: DATA STRUCTURES

Q11. Difference between List and Tuple

Q12. When should you use tuples?

Q13. What is a Dictionary?

Q14. How does dictionary work internally?

Q15. What is Hash Collision?

Q16. What is Set?

Q17. List Comprehension vs Loop

Q18. Time Complexity of List Operations

Q19. Difference between append() and extend()?

Q20. Explain slicing.

MODULE 3: OBJECT ORIENTED PROGRAMMING

Q21. What is OOP?

Q22. What is a Class?

Q23. What is an Object?

Q24. What is Constructor?

Q25. What is Encapsulation?

Q26. What is Inheritance?

Q27. Types of Inheritance?

Q28. What is Method Overriding?

Q29. What is Polymorphism?

Q30. What is Abstraction?

MODULE 4: FUNCTIONS

Q31. What are *args?

Q32. What are **kwargs?

Q33. What is Lambda?

Q34. What is map()?

Q35. What is filter()?

MODULE 5: EXCEPTION HANDLING

Q36. What is Exception?

Q37. Exception Handling Syntax

Q38. Difference between Exception and Error?

Q39. What is Finally?

Q40. How to create custom exception?

MODULE 6–20 (ADVANCED/SENIOR LEVEL)

GENERATORS & ITERATORS

DECORATORS

CONTEXT MANAGERS

THREADING & MULTIPROCESSING

ASYNCIO

MEMORY MANAGEMENT

PYTHON INTERNALS

DATABASES

FASTAPI / FLASK

NUMPY

PANDAS