Habits That Drive Success for Amazon Engineers

I'm a Software Engineer working at AWS, with over 7 years experience. The last few years of my life has taught me a lot. If I could talk to my younger self or any other junior engineer for that matter, here's what I would tell them:  [1] Learn fundamentals, not frameworks. Frameworks change quickly, but core concepts stay with you your whole career. Strong fundamentals make you adaptable, confident, and effective anywhere. [2] Design before coding. If you can’t explain your solution clearly, then the implementation will be unclear too. Draw it. Write it. Challenge it. Then build it. Good design reduces rework and gives you a direction worth building. [3] Read code, not just write it. Study the systems you work in and understand why things were built the way they are. Reading code builds real context — and context makes you faster, wiser, and more effective. [4] Write for humans first, computers second. Choose clear names, small functions, and simple logic, and follow the practices set by your team and engineers before you. Maintainable code makes everyone’s job easier. [5] Know when not to build. Not everything needs more code, sometimes the best solution is removing or reusing what already exists. Favour simplicity, avoid premature abstractions, and keep your systems lean. Code is a liability. [6] Write things down. Design docs, architecture notes, and thoughtful PR descriptions show your thinking. Writing brings clarity, and clarity helps the entire team move faster. [7] Don’t shy away from operations / devops. Many engineers avoid this work, but understanding how your code runs in production is one of the most important parts of the job — build it, own it, run it. It leads to safer judgement. [8] Become great at debugging. Most engineers can build features, but not many fewer can fix issues under pressure. Learn how to troubleshoot calmly using logs, tracing and systematic problem solving. [9] Own your career path. If you’re in a job that doesn’t help you grow, work with your manager to change that. If things still don’t improve, find a place that supports your goals. Your career is yours to steer. [10] Communicate clearly and earn trust. Be honest about what you know and what you don’t. Listen carefully, share progress early, and follow through on what you promise. [11] Keep pushing yourself and don’t give up too quickly. There will be tough days and difficult problems. Stay patient, and keep pushing through. Growth often happens right after things start feeling uncomfortable. Resources to level up as software engineer: → The Pragmatic Engineer with Gergely Orosz for industry insights. → System Design One by Neo Kim for system design fundamentals. → Coding Challenges with John Crickett for real world project ideas. → Connect with engineers like Anton Martyniuk, saed, Alexandre Zajac, Demitri Swan, Sanchit Narula, Daniel and Mohamed A. for daily engineering wisdom. #softwareengineering

One habit I built during my early days was to read design docs, even if they did not belong to my team ⚡ The first thing I did after joining Amazon, back in 2016, was to go through their internal Wiki portal. The portal hosted all the public design docs and documentation written by various teams. The portal was a goldmine of information. One thing that I absolutely love about design docs is how practical they are. The designs are not just some random set of boxes drawn on a piece of paper, but rather they contain highly practical approach to solving a problem and the solution will be shipped to production. With multiple engineers writing them and several tech leads reviewing them, these docs hold all the required context, trade-offs made, alternate designs, implementation nuances, and potential pitfalls. Reading them gives a deeper understanding of the domain, the problem, and the system. To be honest, I was initially quite overwhelmed reading them. But over time I got used to it and started connecting the dots. So, if you try to do this, do not be discouraged by the initial complexity, because things will get easier over time. So, if your company also practices writing design docs, do spend time reading them, even if they are from different teams. If not, then be the one who initiates and drives this process. Forming a habit of reading design docs consistently, rewired my thought process and made me a better engineer; hence I would highly recommend you pick this habit up. ⚡ I keep writing and sharing my practical experience and learnings every day, so if you resonate then follow along. I keep it no fluff.

99% of high-performing software engineers I’ve worked with in the last 19 years of my career at Google, Paytm, Amazon, and startups had this one habit that made them stand out: → They used to build prototypes. Fast. Frequently. Even if they’re throwaway. It’s so much easier to reason about a real demo or code sample than to argue endlessly about abstract ideas. 🔁 Building trumps theorizing, every single time: ∟ A quick proof-of-concept > A detailed architecture doc You’ll find edge cases, constraints, and blockers in minutes, not weeks. ∟ 30 lines of code > 3 hours of debate Nothing kills overthinking faster than seeing something actually run. ∟ “Let me show you” > “Let’s brainstorm on a whiteboard” Teams align faster when they see a prototype in action, not just sketches and talk. ∟ One-day spike > Week-long design meetings Most teams need signals and feedback, not another round of speculation. ∟ Even a failed prototype > Weeks of “What if…” Because a failed demo answers more questions than a month of guessing. The best engineers get this: → Shipping something, even if it’s ugly, is the fastest way to stress-test your assumptions and bring others onboard. The feedback you get from a live prototype is 10x more valuable than a week of endless discussion. That’s how you cut through noise. That’s how you lead as an engineer.

10 years ago, I had my first day at Amazon. Amazon allowed me to succeed as an inventor. Here are 10 things you need to know to become an inventor: 1) “No” means “Not yet” When you present an idea, “no” means “Work harder to convince me.” If you give up on your idea, the decision maker will move on because they have 1 million other things to do. It is your job not to accept the “no” and understand that it means you have more work to do. 2) Own your growth No one else will advocate for your idea unless you convince them. You are in charge of pushing your idea (and yourself) along, so if you need resources, you must seek them out and win them. 3) Customer obsession This is an Amazon Leadership Principle, but what I learned is that customer trust doesn’t have a number value. You can’t always measure it, but you have to prioritize it. If a specific action loses money but wins customer trust, it is the right action in the long term. And, if a specific action doesn’t explicitly benefit the customer, you need to wonder why you are doing it. 4) Frugality Another Leadership Principle- Frugality in an innovative culture is NOT simply maintaining the lowest costs. It is getting to the goal even when resources are limited. Focus on the goal first. The frugal approach needs to be effective and efficient, not just chasing low numbers 5) Ownership (Be a doer - don’t wait for the perfect time) To innovate you have to own the problem and the solution. Understand what is going to move the needle long-term and make it happen. 6) Writing Learning to write well was so hard that it made me want to quit Amazon. 10 years later it, has been essential in getting support for Amazon Key. Learn to write so that people read the whole message and don’t have follow-up questions. Make it interesting AND thorough. 7) “The Art of Small Wins” Even slight progress matters, and compounding small wins lead to success. Don’t get so hung up on the big goal that you get distracted from the small wins and the momentum. 8) Don’t make enemies Innovation is a team game. If you have an idea, you will need support. Every enemy you make can be a roadblock. Don’t view innovation as a zero-sum game. This will build a culture of support that will benefit your idea. 9) Active listening Just “listening” isn’t good enough to create an innovative culture. Everybody on the team should feel like their ideas are considered. Take action on the ideas your team shares. 10) Pivot I didn’t show up to Amazon with the idea for Amazon Key. I kept looking for ways to solve problems. This led me through different ideas before landing on something innovative. Getting it wrong at first is necessary to build something new. I am grateful to my team, managers, mentors, friends, and family for supporting me throughout this journey and investing in ideas. Thank you to #Amazon for being the best place on earth to invent. Here's to 10 more years! 🎉

What I would tell my younger self after 10.5 years at Amazon… 1. Ownership > Effort Hard work is table stakes. What sets you apart is ownership. Don’t just flag problems - fix them. Don’t just execute a plan - shape it. Top performers don’t wait for guidance. Biggest leaps in my career are when I took ownership over something, when I drove it, when I proposed the idea. 2. Communicate like a leader (at any level) You can have the best idea in the room, but if you can’t structure it clearly, tailor it to your audience, and deliver it with confidence, it won’t land. Communication isn’t nice to have - it’s the skill that earns trust, gets buy-in, and accelerates your career. I would have invested in it earlier and more, instead of being forced to learn it via Amazon’s writing culture. 3. Design your role, don’t just do your role Your job description is a starting point, not a ceiling. The most impactful moments of my career came when I carved out new opportunities - launching org-wide training programs, creating workstreams to solve a problem, shaping roles that didn’t exist before. Don’t wait for someone else to define your path. What else would you tell your younger self?

I am a senior Data engineer at Amazon with 7+ years of experience. If I could sit down with a junior in Data, here are some good pieces of advice I would tell them that my seniors told me. Start simple. 1. Daily batch jobs? A cron scheduler is enough. You don’t need Airflow for everything. Complexity should be earned, not assumed. 2. Own your pipelines like production code. If your data is consumed across teams or feeds real-time products, treat it like software. Use DAGs, define SLAs, and log everything. 3. Tools are easy. Trade-offs are not. Snowflake and BigQuery are great for ad-hoc analysis. But for high-throughput systems, you’ll need serious tuning, caching, partitioning, pruning, the works. 4. Schema changes are dangerous. They don’t just break dashboards, they can break trust. Use contracts. Validate upstream assumptions. Think like a platform owner. 5. Monitoring is not optional. If your pipeline fails once and no one notices, that’s a miss. If it fails and nobody knows why, that’s a disaster. Build observability early. 6. Spark is powerful and unforgiving. You can move terabytes of data or crash your cluster. Learn how shuffles work. Understand partitioning. Tune before you scale. 7. . APIs will fail. Retries, deduping, and idempotency aren’t optional, they’re survival tools. Treat external data like it’s unreliable by default. 8. Data quality depends on context. Reporting pipelines? Focus on cost. Real-time ML systems? Focus on accuracy and latency. Your design goals should match your business impact. No fancy certification can replace this. These are the lessons you only learn by building real systems, breaking them, fixing them, and owning the fallout. You want to stand out? Start by thinking like the person who has to clean up what you ship. — P.S.: If you like this post, you will like my upcoming livestream session with Zach Wilson even more! I’ll be talking about my journey in Data, the lessons I’ve learned, and a few stories I’ve never shared before on the crazy 24-hour livestream that Zach has organized! Date: 23 May Time: 7: AM (PST), and 7.30 PM (IST) Here’s the link. https://lnkd.in/geVUZfh9 Be sure to join in, you don’t want to miss this.

It's been almost 3 years since I started at Amazon. 10 software engineering golden rules I learned: 0. Tackle complex tasks early. Don't leave hard problems for later. 1. Don't overlook CI/CD, it's your biggest ally. Fight for it if you have to. 2. There are no universal solutions. Evaluate tradeoffs for each context. 3. Persist data first, then build up the UI. Don't do top-down development. 4. Reduce friction in code and systems. Spend time to minimize complexity. 5. Keep coupled components together. Don't break dependencies across repos. 6. Requirements drive development. Nail them down before coding. 7. Take shortcuts only as deadlines approach. Clean them up after. 8. There are no silver bullets in coding. Focus on readability. 9. Use Java. Java is not sexy, but it's good, fast, and scales. What did I miss? #softwareengineering #coding #programming

The Most Valuable Skill I Learned at Amazon (And It’s Not Technical) When I first joined Amazon, I thought my value hinged on having immediate answers and deep technical knowledge. If I didn’t know something right away, I felt like I was falling behind. Then I noticed something interesting. The true experts—the ones everyone trusted—didn’t always have answers immediately. But they always knew how to find them. That’s when it hit me: Being resourceful beats being all-knowing. Here’s how I built resourcefulness into my routine: 1️⃣ A Living Q&A Document Every time I faced a tough question I couldn’t answer right away, I wrote it down—along with how I eventually figured it out. Over time, this became my personal knowledge base, full of real-world solutions instead of theory. 2️⃣ Ask Better Questions I shifted from “Who can I ask for the answer?” to “Who can point me to the right resources?” This small change made a big difference in how quickly I could find information. 3️⃣ Leverage the Network, Not Just A Search Engine Sometimes, the answer isn’t in a document—it’s in someone’s head. I started reaching out directly to colleagues who’d been through similar challenges. Those 15-minute chats often saved me hours of research. The real skill I’ve learned? Resourcefulness. It’s not about knowing everything—it’s about knowing how to figure things out. How do you handle questions you can’t immediately answer? #ContinuousLearning #Resourcefulness #Amazon #CareerGrowth

Lessons from the Trenches: What I've Learned as a Principal Engineer in Amazon Search Amazon's [Principal Engineer tenets](https://lnkd.in/eHtuzWMA) provide valuable guidance that comes alive when applied to specific challenges. Let me share how three experiences taught me what these principles mean for me in practice. Early at Amazon, I noticed our search and catalog systems weren't speaking the same language. Search was built for shoppers while catalog served sellers, creating a disconnect in how we understood products. When customers searched, we struggled to connect their intent with the right items. "Technical Fearlessness" meant proposing an overhaul of data flow between these systems rather than continuing with incremental fixes. This required questioning established patterns across multiple organizations. "Leading with Empathy" became essential as teams brought different perspectives. I discovered even basic terms meant different things to different groups. By actively listening and rephrasing in my words—"So what you're saying is XYZ?"—I built bridges between viewpoints. This wasn't just about being nice; it created the shared understanding necessary for technical progress. Another experience taught me about being "Balanced and Pragmatic." After analyzing tens of millions of search queries to understand the filters that customers encountered, I found quality issues invisible in our averaged metrics and aggregated dashboards. We developed fixes but faced a choice: wait for a sustainable solution or deliver immediate improvements. We chose customer experience, rolling out enhancements while confirming their value through testing, then building sustainability afterward. Sometimes the best technical decision isn't the most elegant—it's the one serving customers now while creating space to build properly for the future. Finally, "Learn, Educate, Advocate" took on new meaning with AI's evolution. Realizing I was behind on AI coding tools, I jumped directly into practice—progressing from basic prompts to Q CLI. This led to building a server in one-tenth the usual time, revealing how we might boost productivity across our engineering work. These experiences showed me that Amazon's PE tenets gain meaning through application—practical guides that help navigate complex technical challenges while focusing on delivering better experiences for customers.