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As a senior engineer, I have interviewed numerous candidates and helped make 10+ successful, lasting hires across multiple organizations and technology industries.<br><br>As an applicant, I have successfully landed positions across … Read More
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I have created interviews banks at Amazon and Google and can help understand how the companies hire and how to prepare. Read More
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Conducted 10s of interviews at Amazon and have experience in the Amazon interview process. Let's have a mock interview so you feel better prepared! Read More
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As a leading software engineer in Amazon AWS, I conducted many interviews for all teams. I personally never failed an interview to land myself a job. I prefer to help … Read More
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As a hiring manager I have decades of experience and have interviewed 100's of candidates and sat in multiple hiring calls. Connect with me to learn the traits and tactics … Read More
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As a data science manager w/ 6 years experience in interviewing for both data science and data science adjacent roles, I can provide feedback that will help your hone your … Read More
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This post goes over Amazon’s Dynamo paper that was the foundation of today’s various key value stores like Cassandra. This is a very good paper to read to get introduced to various distributed system concepts and to me feels like one of those rare papers that are easy to read and understand.
This blog post talks about my learnings as a software engineer while working at a fast paced company like Amazon. These were critical to my continuous growth over the last decade.
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Get the inside scoop on current Amazon interview questions. Prepare for your interview with a few select questions you might face.
To maintain accuracy in my work, I rely on a three-step process that has always served me well. The first step is planning. Before I delve into the task at hand, I plan out my work process, sketch out timelines, and breakdown the task into manageable segments. The second step is execution, where I follow the plan, ensuring that I'm detailed in my work. For example, when working with data, double-checking figures, cross-verifying sources, and correctly documenting everything are all part of this step. The final step is review. No matter how careful I am, human error is inevitable, and a comprehensive review helps to catch these. I go through the work, verify all details again, and if time permits, I leave it aside and review again after a while with a fresh mind. This approach has consistently helped me maintain high accuracy in my work.
While working as a Marketing Manager at XYZ Company, I had the opportunity to lead a substantial holiday campaign. We had a range of products to promote, but a limited budget. To optimize our spending, I turned to historical sales data to identify which products consistently attracted the most interest during the holiday season. It was crucial to examine the data thoroughly to understand trends and patterns. Based on the data, we were able to identify the top-selling products and focus our promotional budget on marketing those. Equally as important, we also identified products with lower popularity, helping us avoid wasteful spending. Consequently, our strategic campaign resulted in a significant boost of over 20% in our sales compared to the previous year, reaffirming the impact of data-driven decisions.
At my previous job, I was working as a Customer Service Representative where our primary responsibility was troubleshooting the software issues our customers encountered. I remember an instance where a customer was quite irritated because he'd been dealing with an ongoing issue for several days. This had affected his work, and he was understandably frustrated. I calmly let him express his feelings, after he had done that, I apologized for the inconvenience and reassured him that I was there to help solve his issue. I patiently asked targeted questions to identify the root of his problem. After understanding his issue, I walked him through the steps to fix the problem. It took longer than it usually would, but in the end, he was able to resolve his issue successfully. Not only was he appreciative of the solution but he was also happy with the way I dealt with the situation, staying patient and guiding him through each step. It was a rewarding experience that underscored the importance of empathy and patience in customer service.
Despite having a well-rounded team in my previous role, there were instances of disagreement. During one project, a colleague and I had a conflicting perspective on the project's direction. I believed in taking a more conservative, well-tread path, while he wanted to experiment with a new approach. When we realized we couldn't agree, we decided to sit down and address the issue directly. We both presented our views, made sure to listen to each other, and brought in the data we had to support our views. We discussed the pros and cons of each approach, considering all potential outcomes. Seeing the benefits and potential in my colleague's ideas made me reassess my stand and agree to try the newer approach. It’s vital to remember disagreements in a team setting aren't necessarily bad; they often lead to better solutions if adequately addressed.
While leading the sales team at a previous company, I noticed there were inefficiencies in how the team was managing sales leads. To improve this, I recommended implementing a sophisticated CRM tool. I believed it would streamline the process, improve organization, and ultimately, raise sales numbers.
However, the tool had a steep learning curve, and the team struggled to adopt it. Despite providing training sessions, the team was spending more time learning to navigate the system than actually selling. Moreover, maintaining the CRM turned out to be more resource-intensive than anticipated. As a result, productivity decreased rather than increased in the weeks following the implementation.
Recognizing that the plan wasn't working as intended, I arranged for a team meeting to openly discuss the issues being faced. Based on the team's feedback, we decided to pivot our approach. We opted to continue using the CRM for certain functionalities that worked well, but returned to tried-and-true processes for tasks that were overly complicated by the new tool. As a result, we were able to regain our productivity, while still benefiting from the useful features that the CRM offered. This experience reminded me of the importance of not just considering the technological capabilities of a tool, but also the ease of use and the impact on the team's workflow.
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