Technical Interview Preparation: Complete Guide

Technical interviews can be challenging, but with the right preparation strategy, you can walk in confident and showcase your abilities. This guide covers everything from resume optimization to acing the final rounds.

The Interview Process

Most tech companies follow a similar hiring process:

Application/Referral: Resume screening
Recruiter Screen: 15-30 min call about background and role
Technical Phone Screen: 45-60 min coding interview
Onsite/Virtual Interviews: 4-6 hours of interviews
- 2-3 coding rounds
- 1 system design round (for senior roles)
- 1-2 behavioral rounds
Offer/Negotiation: Compensation discussion

Resume & Application

Resume Best Practices

One page: Unless you have 10+ years of experience
Clear format: Easy to scan, consistent styling
Action verbs: Led, Built, Improved, Implemented, Designed
Quantify impact: Numbers make achievements concrete
Relevant skills: Match job description keywords
No typos: Have others proofread

Writing Strong Bullet Points

❌ Weak: "Worked on the search feature"

✅ Strong: "Implemented full-text search using Elasticsearch,
reducing query latency by 60% and improving user engagement by 25%"

Formula: [Action Verb] + [What You Did] + [Technology/Method] + [Impact/Result]

Examples:
• Reduced API response time by 40% by implementing Redis caching layer
• Built CI/CD pipeline using GitHub Actions, cutting deployment time from 2 hours to 15 minutes
• Led migration of 500K users from legacy system to microservices architecture
• Mentored 3 junior developers, resulting in 2 promotions within 6 months

Resume Sections

Contact Info: Name, email, phone, LinkedIn, GitHub, portfolio
Summary (optional): 2-3 sentences for experienced candidates
Experience: Most recent first, 3-5 bullet points each
Projects: Especially important for new grads
Education: Degree, school, graduation year, relevant coursework
Skills: Languages, frameworks, tools (avoid rating yourself)

Coding Interviews

Coding interviews test your problem-solving ability, coding skills, and how you communicate your thought process.

Key Topics to Master

Topic	What to Know	Common Problems
Arrays/Strings	Traversal, two pointers, sliding window	Two Sum, Valid Anagram, Longest Substring
Hash Tables	O(1) lookup, counting, grouping	Group Anagrams, LRU Cache
Linked Lists	Traversal, reversal, fast/slow pointers	Reverse List, Detect Cycle, Merge Lists
Trees	BFS, DFS, traversals, BST operations	Max Depth, Validate BST, Level Order
Graphs	BFS, DFS, topological sort, shortest path	Number of Islands, Clone Graph
Dynamic Programming	Memoization, tabulation, state transitions	Climbing Stairs, Coin Change, LCS
Sorting/Searching	Binary search, merge sort, quick sort	Search Rotated Array, Merge Intervals

Problem-Solving Framework

1. UNDERSTAND (2-3 minutes)
   • Repeat the problem back
   • Ask clarifying questions
   • Confirm input/output format
   • Discuss edge cases

2. PLAN (3-5 minutes)
   • Think out loud
   • Consider multiple approaches
   • Analyze time/space complexity
   • Choose approach and explain why

3. IMPLEMENT (15-20 minutes)
   • Write clean, readable code
   • Use meaningful variable names
   • Comment if logic is complex
   • Keep talking through your code

4. TEST (3-5 minutes)
   • Walk through with a simple example
   • Test edge cases (empty, single element, duplicates)
   • Fix bugs if found

5. OPTIMIZE (if time permits)
   • Discuss potential improvements
   • Trade-offs between time and space

Example Problem Walkthrough

Problem: Given an array of integers, return indices of two numbers that add up to target.

Step 1: UNDERSTAND
"So I need to find two different numbers in the array that sum to the target,
and return their indices. Can there be multiple valid pairs? Should I return
the first one found? Can the array have duplicates?"

Step 2: PLAN
"Brute force would be O(n²) with nested loops. But I can use a hash map to
store numbers I've seen, giving O(n) time and O(n) space."

Step 3: IMPLEMENT

def two_sum(nums, target):
    seen = {}  # value -> index

    for i, num in enumerate(nums):
        complement = target - num

        if complement in seen:
            return [seen[complement], i]

        seen[num] = i

    return []  # No solution found

Step 4: TEST
"Let me trace through [2, 7, 11, 15] with target 9:
- i=0: num=2, complement=7, not in seen, add 2:0
- i=1: num=7, complement=2, 2 IS in seen at index 0
- Return [0, 1] ✓"

Step 5: OPTIMIZE
"This is already O(n) time and O(n) space. We could sort and use two pointers
for O(n log n) time and O(1) space if we didn't need indices."

System Design

System design interviews assess your ability to design large-scale systems. They're typically asked for senior or mid-level positions.

System Design Framework

1. REQUIREMENTS (5 minutes)
   Functional: What should the system do?
   Non-functional: Scale, latency, availability, consistency

2. ESTIMATIONS (5 minutes)
   Users, requests/second, storage needs, bandwidth

3. HIGH-LEVEL DESIGN (10 minutes)
   Draw main components: clients, servers, databases, caches

4. DETAILED DESIGN (15 minutes)
   Dive deep into 2-3 components based on interviewer interest

5. SCALING & TRADE-OFFS (10 minutes)
   Identify bottlenecks, discuss solutions, trade-offs

Key Concepts

Concept	What to Know
Load Balancing	Round robin, least connections, consistent hashing
Caching	CDN, Redis/Memcached, cache invalidation strategies
Databases	SQL vs NoSQL, sharding, replication, indexing
Message Queues	Kafka, RabbitMQ, async processing
Microservices	Service boundaries, API design, communication patterns
CAP Theorem	Consistency, Availability, Partition tolerance trade-offs

Common System Design Questions

Design a URL shortener (like bit.ly)
Design Twitter/Instagram feed
Design a chat application
Design a rate limiter
Design YouTube/Netflix
Design Uber/Lyft
Design a search autocomplete system
Design a distributed cache

Behavioral Questions

Behavioral interviews assess soft skills, culture fit, and how you've handled past situations. Use the STAR method to structure your answers.

The STAR Method

S - Situation: Set the context (brief)
T - Task: What was your responsibility?
A - Action: What specifically did YOU do?
R - Result: What was the outcome? (quantify if possible)

Example:
Q: "Tell me about a time you had a conflict with a teammate."

S: "On my last project, a senior developer and I disagreed about
   whether to use GraphQL or REST for our new API."

T: "As the tech lead, I needed to make a decision that the team
   could align on while considering both technical and timeline constraints."

A: "I organized a meeting where we both presented our cases with
   concrete criteria: learning curve, team familiarity, and project
   requirements. I created a decision matrix and we evaluated each
   option objectively."

R: "We chose REST due to team expertise and tighter deadline. The
   senior dev appreciated the fair process, and we delivered on time.
   We documented GraphQL as a future consideration."

Common Behavioral Questions

Tell me about yourself (have a 2-minute pitch ready)
Why do you want to work here?
Describe a challenging project you worked on
Tell me about a time you failed/made a mistake
How do you handle disagreements with teammates?
Describe a time you had to learn something quickly
Tell me about a time you went above and beyond
How do you prioritize when you have multiple deadlines?
Where do you see yourself in 5 years?
Do you have any questions for me? (always ask questions!)

Questions to Ask Interviewers

About the role:
• What does a typical day look like?
• What would success look like in the first 90 days?
• What are the biggest challenges facing the team?

About the team:
• How is the team structured?
• What's the code review process like?
• How do you handle technical debt?

About growth:
• What learning opportunities are available?
• How does the promotion process work?
• Can you tell me about someone who's grown in this role?

About culture:
• How would you describe the engineering culture?
• What do you enjoy most about working here?
• How does the team celebrate wins?

Practice Strategy

Study Plan (8-12 weeks)

Weeks	Focus Area	Goals
1-2	Fundamentals	Review data structures, Big O, basic patterns
3-4	Arrays, Strings, Hash Tables	50+ problems, master common patterns
5-6	Trees, Graphs, Recursion	40+ problems, BFS/DFS fluency
7-8	Dynamic Programming	30+ problems, recognize DP patterns
9-10	System Design	Study 5-6 systems, practice explaining
11-12	Mock Interviews	2-3 mock interviews per week

Daily Practice Tips

Consistency beats intensity: 1-2 problems daily is better than cramming
Time yourself: 20-25 minutes for medium problems
Review solutions: Understand multiple approaches
Explain out loud: Practice articulating your thought process
Track progress: Keep a log of problems solved and patterns learned
Revisit problems: Redo problems after a week to reinforce learning

When You're Stuck

Try for 20 minutes before looking at hints
Look at the hint, then try again
If still stuck after 10 more minutes, read the solution
Understand the solution completely
Implement it yourself without looking
Add the problem to your review list

During the Interview

Before the Interview

Test your setup (camera, microphone, IDE/whiteboard)
Have water nearby
Review the job description and company
Prepare your "tell me about yourself" response
Get a good night's sleep

During the Interview

Think out loud: Interviewers can't read your mind
Ask questions: Clarify requirements before coding
Start simple: Get a working solution, then optimize
Test your code: Walk through examples manually
Stay calm: Getting stuck is normal, talk through it
Be coachable: Listen to hints and adapt

What Interviewers Look For

Problem solving: Can you break down complex problems?
Coding ability: Can you write clean, correct code?
Communication: Can you explain your thinking clearly?
Coachability: Do you respond well to hints and feedback?
Culture fit: Would you be enjoyable to work with?

Practice Resources

Coding Practice Platforms

LeetCode: Most comprehensive, great for FAANG prep
HackerRank: Good for beginners, company-specific tests
CodeSignal: Used by many companies for assessments
AlgoExpert: Curated problems with video explanations
Exercism: Free, mentor-reviewed exercises

System Design Resources

Designing Data-Intensive Applications (book by Martin Kleppmann)
System Design Interview (book by Alex Xu)
ByteByteGo (YouTube channel)
Grokking the System Design Interview (course)

Mock Interview Platforms

Pramp: Free peer-to-peer mock interviews
Interviewing.io: Practice with engineers from top companies
Exponent: Product and system design mocks

Curated Problem Lists

Blind 75: 75 essential problems covering all patterns
NeetCode 150: Expanded list with video solutions
LeetCode Top Interview Questions: Company-specific lists

Final Tips

Don't memorize solutions: Understand patterns and principles
Quality over quantity: Deep understanding beats surface coverage
Practice under pressure: Mock interviews are invaluable
Take care of yourself: Sleep, exercise, and breaks matter
Rejection is normal: Even great engineers fail interviews
Keep learning: Every interview is a learning opportunity

Next Steps

Algorithms - Review essential algorithm patterns
Data Structures - Master fundamental data structures