Common Tech Interview Questions to Expect

After 15+ yrs interviewing and hiring at Fortune 500 companies, here's what I know: The difference between good and great candidates isn't talent. It's preparation. Here are the 12 must-prepare questions I've asked or seen being asked in interviews (and how to nail them): 💥 "Tell me about yourself" → Not your life story. Your career movie trailer: Hook, highlights, where you're headed (2 mins max). 💥 "What makes you different?" → Pick 3 strengths that solve their problems (I'll teach you how to find these). 💥 "Your biggest weakness?" → Be real. I've heard every "perfectionist" story. Show self-awareness and growth instead. 💥 "Why us?" → If you can't articulate this clearly, you're not ready. Research isn't optional. 💥 "Tell me about a challenge" → Use the STAR method: Situation, Task, Action, Result. Keep it recent and relevant. 💥"How do you handle mistakes?" → Everyone fails. Winners show ownership and learning. 💥 "Managing multiple priorities?" → Concrete example + your system. Show me your mind works strategically. 💥 "Dealing with conflict?" → Focus on resolution, not drama. Emotional intelligence wins here. 💥 "Ethical decisions?" → Values matter more than outcomes. Pick a story that shows your compass. 💥 "Why leave your current role?" → Growth story, not escape story. Never bash your employer. 💥 "Missing a deadline?" → Ownership + Learning + Prevention. Three-part answer. 💥 "Your greatest strength?" → Match their needs. The job description is your cheat sheet. 🔥 Pro Secret: Record yourself answering these. You'll hear what needs work. The goal isn't memorization. It's authentic confidence. Save this cheat sheet. Your next interview could be tomorrow. 🔁 REPOST to help someone else get hired. 👤 FOLLOW for more practical job search content that works.

I was chatting with a backend interviewer ... ... and I picked his brain about what he expects from candidates. Here are 8 items he is always looking at: 1. Programming Language Proficiency He expects candidates to know their primary backend language inside and out: Python, Java, C#, it doesn't matter. The more senior the role, the more he dives into advanced topics like memory management, concurrency, and language-specific features. 2. Database Knowledge He always checks if candidates are comfortable with SQL databases. Be ready to chat about query optimization, schema design, and concepts like indexing and transactions. 3. APIs & Web Services He loves asking about API design. Candidates should know how to build RESTful APIs, why other options exist (GraphQL), and how to handle authentication (think OAuth). Expect questions on rate limiting, API versioning, and even webhooks. 4. System Design Even for junior roles, he tests candidates on system architecture. You'll need to explain how to design systems for scalability, fault tolerance, and high availability. He's big on event-driven architecture. 5. Security Security is a non-negotiable. He'll ask about SQL injection, XSS, CSRF, and how you secure APIs. If you don't mention data encryption, input validation, or authentication best practices, that's a red flag for him. 6. Testing & Debugging He expects candidates to know how to write unit tests at a minimum. 7. Data Structures & Algorithms You don't need to be a LeetCode wizard, but understanding Big-O complexity and knowing when to use hash maps, trees, or queues will help you stand out. 8. DevOps & Deployment Basics He doesn't expect you to be a DevOps expert, but he'll definitely ask about CI/CD pipelines, Docker, and deploying apps on cloud platforms like AWS, Azure, or GCP. The best way to learn these topics is to build actual products. Try to bring your ideas to life, eventually, you'll hit most of these.

Hard Truth: Data Structures - The Unavoidable Interview Reality Here's a pattern I've noticed recently that every software professional needs to hear: Even if you haven't used a binary tree in years, you WILL face data structure questions in your next interview. Here's why this matters: The Interview Reality Check: 1. FAANG-level companies:    - Will absolutely grill you on data structures    - Expect implementation from scratch    - Want optimal solutions 2. Startups:    - May seem more relaxed    - Still include DS questions in their process    - Use them to evaluate problem-solving 3. Even Frontend Roles:    - React state management? That's a tree    - Event handling? Welcome to queues    - Browser history? That's a stack What I've Observed: - Brilliant developers failing interviews because they're rusty on basics - Senior engineers stumbling on LinkedList questions - Tech leads getting rejected for missing optimal solutions The Smart Approach: 1. Keep a "DS Emergency Kit":    - Arrays & String manipulation    - Hash Tables implementations    - Tree traversals    - Graph basics    - Stack & Queue operations 2. Monthly Refresh Routine:    - Solve one problem per structure    - Review time complexities    - Practice explaining your approach Common Mistakes: - Thinking "I don't use this at work, so I won't study it" - Starting interview prep too late - Focusing only on coding, ignoring theory Quick Tips: 1. LeetCode Medium is your friend 2. Always write clean code in interviews 3. Think aloud during problem-solving 4. Review basic implementations monthly Core Data Structures You MUST Know: 1. Arrays    - What: Continuous memory blocks    - Why: Foundation of most data operations    - Real use: Instagram's photo feed, Spotify's playlist management 2. Linked Lists    - What: Connected nodes with next/prev references    - Why: Dynamic memory allocation    - Real use: Undo/Redo functionality in text editors 3. Hash Tables    - What: Key-value pair storage    - Why: Lightning-fast O(1) lookups    - Real use: Database indexing, caching systems 4. Stacks (LIFO)    - What: Last-In-First-Out structure    - Why: Track execution context    - Real use: Browser history, Function call management 5. Queues (FIFO)    - What: First-In-First-Out structure    - Why: Order preservation    - Real use: Print spoolers, Message queues in distributed systems 6. Trees    - What: Hierarchical data structure    - Why: Organized data relationships    - Real use: File systems, DOM in web browsers 7. Graphs    - What: Nodes connected by edges    - Why: Complex relationship mapping    - Real use: Social networks, Google Maps, Netflix recommendations 1. Practice implementing from scratch 2. Study time complexity for each operation 3. Learn when to use which structure Action Items: 1. Pick one structure weekly 2. Implement it in your preferred language 3. Solve 2-3 related problems 4. Document real-world applications