Aryan Singh

Why Every Tech Candidate Needs an 𝗢𝗻𝗹𝗶𝗻𝗲 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 Most candidates think portfolios are only for designers. Not true. If you’re aiming for a role in a top tech company, your online presence can be a game-changer. In fact, recruiters often source directly from online profiles before you ever apply. The right portfolio can make opportunities come to you. Here’s how to build one that stands out: 𝟭. 𝗖𝗿𝗲𝗮𝘁𝗲 𝗮 𝘀𝗶𝗺𝗽𝗹𝗲 𝘄𝗲𝗯𝘀𝗶𝘁𝗲. It doesn’t have to be fancy. A single-page site with your resume, a short bio, a professional picture, and a list of projects is enough to showcase who you are. This becomes your digital business card. 𝟮. 𝗦𝗵𝗼𝘄𝗰𝗮𝘀𝗲 𝘆𝗼𝘂𝗿 𝘃𝗼𝗶𝗰𝗲. Start a blog or write about things you’re learning-whether it’s technology, problem-solving approaches, or insights from your journey. Don’t worry about perfection; consistency matters more. You can also contribute guest posts to established blogs, which gives you instant visibility and backlinks to your own site. 𝟯. 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗲 𝘁𝗼 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝘀. Answer questions on forums, LinkedIn, or platforms like Stack Overflow. When you share thoughtful responses, you’re not just helping someone-you’re also building credibility. Recruiters and hiring managers do notice this. 𝟰. 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗲 𝗚𝗶𝘁𝗛𝘂𝗯 (𝗳𝗼𝗿 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀). Get involved in open source projects. Download tools, improve them, fix bugs, or even document them better. Every pull request, issue raised, or contribution you make is public proof of your skills. 𝟱. 𝗧𝗵𝗶𝗻𝗸 𝗹𝗼𝗻𝗴-𝘁𝗲𝗿𝗺. Your online portfolio isn’t just about getting a job. It’s about building a professional brand that grows with you. Over time, these digital footprints accumulate into a powerful signal of expertise. The result? Instead of chasing recruiters, you’ll have recruiters chasing you. The best part: you don’t need to wait for the “perfect project” to begin. Start small, start today, and let your online presence work for you while you focus on leveling up your skills.

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Data is the new oil and Data Engineers are the refineries and most people are still hauling buckets. I've learned a ton by studying practitioners who make complex topics feel obvious and then push you to ship something Zach Wilson community bootcamp is an unfair advantage. The "Absolutely Free Beginner Data Engineering Boot Camp" plus the Community Edition modules turn modelling, Spark, Kafka and real-time pipelines into muscle memory. It's hands-on, zero fluff and still free. Sumit Mittal SQL and Big Data playlists are the clarity I wish college had. You watch a 10-minute window-function explanation and immediately refactor yesterday's query. His interview series quietly teaches you how systems behave in the wild. Krish Naik Big Data Engineering playlist gives you the "why" behind the "how" From Databricks to orchestration to MLOps, he kills the buzzwords and shows you what actually ships. DataTalks Club's DE Zoomcamp by Alexey Grigorev forces end-to-end thinking. You won't just "know about" Docker, dbt, Kafka, and Spark you'll have dashboards, PRs and battle scars. And Andreas Kretz is fundamentals on tap the architecture sense that stops your pipeline from falling over at 10× scale, plus the career advice nobody tells you. If you're serious, steal this tiny playbook Pick one public dataset tonight. Ingest --> model --> validate --> serve, Add a painfully simple dashboard and write a README like an SRE. Post your repo on Monday. Repeat next weekend with one new pattern (SCD, partitioning, a Kafka topic, a dbt test). That cadence compounds faster than any course. If you already follow these creators, you know. If you don't, fix that and start shipping. Save this post, tag the friend who keeps "researching roadmaps" and let’s build.

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Dreaming of Amazon, Google, or any other PBC Offer? These interviews aren’t about chance, they’re about proving you can think, build, and scale like an engineer who belongs in the room. If you want to prepare as per current industry standards, start here- https://bit.ly/4mfeCsk Most interview problems are designed to break your patterns and test your logic. Understand the uncomfortable truth: → If you can’t handle Graphs, Trees, or DP, you won’t even clear the first gate. Most interview problems are designed to break your patterns and test your logic. → Don’t assume system design is “only for seniors.” At SDE-1/2, you’ll still be asked how you’d scale, where to cache, and how to model a DB. Fail here, and you’re out. → Core CS – OS, DBMS, Networks. Ignore them and you’ll regret it when you’re blank in the interview. → Real Dev Skills – Know your language like your life depends on it. Build projects that aren’t “to-do apps” but things that could actually break in production. Now, remember, even the best-prepared engineers get rejected. I’ve seen brilliant devs fail multiple times before making it. But your consistency and resilience will help you reach your goal. Talk to people who made the switch. Platforms like Tutort Academy provide guidance from expert SDEs—a difference that can take your prep from good to offer-ready. So far, they’ve helped 2,150+ professionals switch careers and land their dream roles with lucrative offers. Because at the end of the day, it’s you, your grind, and your choices. #careerswitch #techinterview #dreamcompany #google #tutortacademy

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Coding is going to change forever in a few years, just knowing a particular tech stack or about certain data structures and algorithms won’t cut the deal. More companies will look out for problem solving skills and strong first principle thinking in candidates. Good problem solvers aren’t tied to knowledge, they are able to approach things from first principles and are able to decide how to solve a problem in the best possible way with the available context and tools. Here are some action items to improve problem solving wrt to coding. - Stop trying to memorise - Solve a lot of adhoc Codeforces problems - Solve math problems - Try to see the thought process of other great problem solvers - Learn to give highly contextual prompts to AI tools aiming to get a job done in minimum number of prompts - Don't offload the reasoning/thinking on AI, do it yourself as much as possible - Learn to break tasks into small independent subtasks

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Most people only search for jobs on LinkedIn. That’s a huge mistake. Dozens of better platforms can help you land high-paying remote jobs. Here are 10 websites that pay in USD for remote work: 1. Remote Circle - Helps find remote jobs in your timezone - Covers a variety of industries and roles - Link:https://remotecircle.com/ 2. We Work Remotely - Largest remote work community with 4.5M+ visitors - Offers a wide range of remote job opportunities - Link:https://weworkremotely.com 3. Hubstaff Talent - Free resource for companies looking for remote talent - Connects businesses with freelancers and agencies worldwide - Link:https://hubstafftalent.net 4. Remote Woman - Remote job board tailored for women - Promotes flexibility and career growth - Link:https://remotewoman.com/ 5. Wellfound - Connects job seekers with startups - 130K+ tech jobs from 27K companies - Link:https://wellfound.com/ 6. Remotive - Curates active, fully remote tech jobs - Trusted by top global tech companies - Link:https://remotive.io/ 7. WorkWave - Remote job listings for various industries - Known for flexible work opportunities - Link:https://www.workwave.com/ 8. AI Jobs - Focuses on AI-related remote job listings - Features top 1% of AI companies - Link:https://theaijobboard.com 9. Toptal - Exclusive network for top freelancers - Covers software development, design, finance & more - Link:https://www.toptal.com/ 10. FlexJobs - Find remote jobs globally or near you - Offers career coaching and resume help - Link:https://www.flexjobs.com/ 𝗙𝗥𝗘𝗘 (𝗚𝗼𝗼𝗴𝗹𝗲) 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗿𝗲𝗴𝗿𝗲𝘁 𝗻𝗼𝘁 𝘁𝗮𝗸𝗶𝗻𝗴 𝗶𝗻 𝟮𝟬𝟮𝟱. 🔃10000+ free courses free access: https://lnkd.in/g9qssg4T Google Data Analytics: https://lnkd.in/g-tjpeqe Google Project Management https://lnkd.in/gNAapb_x Foundations of Project Management https://lnkd.in/gP-h_Qpq Google Introduction to Generative AI https://lnkd.in/ggbGgmGP Google Cybersecurity https://lnkd.in/g6qBj_in Google UX Design https://lnkd.in/gcpVd5ng Google Digital Marketing & E-commerce: https://lnkd.in/g2i68zzz Google IT Support: https://lnkd.in/gzvpYfwG Web Applications for Everybody Specialization:  https://lnkd.in/gHQY-yWm Get Started with Python: https://lnkd.in/gV3ArxMj Learn Python Basics for Data Analysis https://lnkd.in/gACaGvYT IBM Full Stack Software Developer Professional Certificate https://lnkd.in/gkmCc3HV IBM Python for Data Science, AI & Development: https://lnkd.in/ggG5suCz IBM Data Science: https://lnkd.in/g-HWyEFk Generative AI for Data Scientists https://lnkd.in/g7KxpMVZ Generative AI for Data Analysts https://lnkd.in/gQQZWJxE Generative AI for Cybersecurity https://lnkd.in/g8rUE_Kt Generative AI for Data Engineers https://lnkd.in/gwuJTctt Microsoft Cybersecurity Analyst Professional https://lnkd.in/gKKfbd8v

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After taking several interviews in the software engineering space, I've noticed a few patterns: both good and not so good. If you're preparing for your next interview, here are a few practical tips that can make a big difference: 💡 1. Think aloud Companies are not just looking for the right answer, they are more interested in how you think. Walk them through your logic. 💡 2. Clarify the problem before jumping in. Don’t assume. Take a minute to ask clarifying questions and define edge cases. It shows maturity and a product-oriented mindset. 💡 3. Clean code > clever code. Readable, maintainable code always wins over overly complex one-liners. Bonus points if you talk about time and space complexity too! 💡 4. Show curiosity, not just competence. Interviews are a two-way street. Ask insightful questions about the team, culture, or tech stack, signal that you're engaged. 💡 5. Don’t panic on unknown questions. It's okay to not know everything. Be honest, explain what you do know, and share how you’d approach learning the rest. At the end of the day, interviews aren’t just about algorithms or system design they’re about communication, collaboration, and problem-solving. #SoftwareEngineering #InterviewTips #CareerGrowth #TechInterviews #Hiring

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Why 90% of Students Fail Online Assessments (And the 5 Fixes That Worked for Me) Confession: I failed 7 OAs before realizing it wasn’t about coding skills – it was about strategy. Here’s what companies don’t tell you: 💥 The 3 Big Reasons Students Fail 1️⃣ The "Perfect Code" Trap Companies often care more about test cases passed than elegant solutions What works: Solve the brute force first, then optimize if time allows 2️⃣ Hidden Time Killers Spending 40 mins on Q1 → rushing Q2 & Q3 Pro tip: Always solve the easiest problem first to clear cutoff 3️⃣ Environment Shock No IDE = 50% slower typing (practice on CodeChef IDE) 🚀 5 Fixes That Got Me 3 Offers 1. The 30-50-20 Rule - 30% time: Read all questions carefully - 50% time: Solve highest-mark questions first - 20% time: Recheck edge cases 2. OA-Specific Prep - Practiced on HackerRank (used by 80% of companies) - Memorized input/output formats for Python/Java 3. The "1-2-3 Debug" Method // Step 1: Print inputs System.out.println("INPUT: " + Arrays.toString(arr)); // Step 2: Track variables System.out.println("SUM: " + runningSum); // Step 3: Test edge cases manually if (arr == null || arr.length == 0) return 0; // Always check empty input! # Step 3: Test edge cases manually if not arr: return 0 # Always check empty input! 4. Cheat Sheet Ready - Had templates for: - Binary search - Graph traversal - Sliding window 5. Post-OA Analysis - Recorded every mistake in a "Dumb Errors" notebook - Example: "Forgot to reset variables between test cases" ⚠️ Common "Smart" Mistakes ❌ Using advanced DS when brute force works ❌ Ignoring constraints (10^5 inputs ≠ O(n²) solution) ❌ Not testing with empty/min/max inputs 👇 What’s Your Biggest OA Struggle? Save this ♻️ for your next OA! Let’s connect and grow together! 🌱🔥- Umesh Kaushik #CampusPlacements #CodingTests #TechJobs #DSA

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After spending 3+ years in tech, here’s one piece of advice I wish someone had told me early on: You don’t become a better engineer by writing more code. You become better by reading the code you regret. Yes — the messy, unscalable, over-engineered code you wrote a year ago. That’s where the real learning happens. Early in my career, I thought growth meant shipping more features, learning more tools, or picking up new frameworks every few weeks. But over time, I realized something deeper: ➡️ Revisiting your old code teaches humility ➡️ Understanding your past decisions sharpens judgment ➡️ Refactoring your own mess teaches you how to write for others The best engineers I’ve worked with weren’t the ones who knew the fanciest libraries. They were the ones who knew how to read code, understand trade-offs, and write in a way others could maintain. So if you’re a fresher, junior dev, or even a mid-level engineer: ✅ Go back to your old GitHub repos ✅ Read through your first few side projects ✅ Refactor something from scratch ✅ Document the mistakes and what you’d do differently It’s not glamorous — but it’s how you grow. I also share real tech career insights, backend engineering breakdowns, and things I’ve learned from actual projects — not just theory: https://lnkd.in/gT7acAgd Abhay Singh 🤝.

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No replies. No interviews. Just silence for 90 days. Then, I ran my resume through ChatGPT. Got 5 callbacks in less than a week-using just 7 prompts. [Save for later] 1. Spot the Flaws Prompt: Act as a recruiter for [your industry/role]. Review my resume below and highlight weak areas, overused buzzwords, and missing metrics. Be brutally honest. 2. Rewrite for Impact Prompt: Rewrite this resume to sound more results-driven, quantifiable, and compelling for [target role]. Focus on achievements, not just duties. 3. ATS Boost Prompt: Update this resume to be fully optimized for Applicant Tracking Systems (ATS) for the role of [specific role/title]. Use industry-specific keywords naturally. 4. Craft My Hook Prompt: Write a powerful, 3-line professional summary that hooks a recruiter in under 10 seconds. Prioritize impact, clarity, and value. 5. Upgrade Experience Prompt: Rephrase the experience section to highlight impact, results, and transferable skills using action verbs and quantifiable outcomes. 6. Format Fix Prompt: Suggest a clean, modern resume format that works for both humans and ATS. No graphics, no columns. Just structured and effective. Google is offering FREE online courses with certification. 𝗙𝗥𝗘𝗘 (𝗚𝗼𝗼𝗴𝗹𝗲) 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗿𝗲𝗴𝗿𝗲𝘁 𝗻𝗼𝘁 𝘁𝗮𝗸𝗶𝗻𝗴 𝗶𝗻 𝟮𝟬𝟮𝟱 🔃10000+ free courses free access: https://lnkd.in/gX7DWrzG Google Data Analytics: https://lnkd.in/g-tjpeqe Google Project Management https://lnkd.in/gNAapb_x Foundations of Project Management https://lnkd.in/gP-h_Qpq Google Introduction to Generative AI https://lnkd.in/ggbGgmGP Google Cybersecurity https://lnkd.in/g6qBj_in Google UX Design imp.i384100.net/JKO94e Google Digital Marketing & E-commerce: https://lnkd.in/g2i68zzz Google IT Support: https://lnkd.in/gzvpYfwG Web Applications for Everybody Specialization: https://lnkd.in/gHQY-yWm Microsoft Power BI Data Analyst https://lnkd.in/d3-VmJQz Microsoft Cybersecurity Analyst https://lnkd.in/dfDPjYQJ Excel Skills for Business Specialization https://lnkd.in/dTufybxQ The Structured Query Language (SQL) https://lnkd.in/dqJFR_mq 🧠 𝐓𝐡𝐞 𝐌𝐨𝐬𝐭 𝐏𝐨𝐰𝐞𝐫𝐟𝐮𝐥 𝐀𝐈 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 𝐘𝐨𝐮 𝐂𝐚𝐧 𝐓𝐚𝐤𝐞 𝐢𝐧 2025 Programming for Everybody https://lnkd.in/gV3ArxMj AI for Everyone by DeepLearning AI https://lnkd.in/gbnP76_B Python for Data Science, AI and Development by IBM https://lnkd.in/ggG5suCz Introduction of AI by IBM https://lnkd.in/gD5iUUi4 IBM Data Science Professional Certificate https://lnkd.in/g-HWyEFk IBM Data Science Professional Certificate https://lnkd.in/g-HWyEFk Google Cybersecurity Professional Certificate https://lnkd.in/g6qBj_in Data Science: Foundations using R Specialization https://lnkd.in/g_2tcy8x Google AI Essentials https://lnkd.in/dCjktipG

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