Okay, I've searched for Data Engineer roles in Seattle that focus on big data and ETL processes, requiring knowledge of AWS, with 1+ years of experience. I have found 57 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Data Engineer I role on the Payment Acceptance & Experience (PAE) team at Amazon requires a foundational understanding of data engineering principles, focusing on the lifecycle of data generation and application. This position is pivotal in developing large-scale, high-performance data structures essential for analytics, reporting, and machine learning. The key responsibilities involve implementing ETL processes, data ingestion routines, and translating business requirements into operable solutions. The ideal candidate will face challenges related to architecture deficiencies and will be effective in problem-solving by building advanced software solutions. Success in this role is often measured by the efficiency of data solutions developed and the ability to contribute meaningfully to the team’s objectives within the fast-paced environment of Amazon, ensuring smooth payment operations for millions of users worldwide. Having a blend of technical skills like SQL and scripting experience, as well as soft skills such as collaboration and communication, is vital due to the need for cross-functional teamwork and the ability to clarify complex information.

Company Analysis:

Amazon is a global leader in e-commerce and technology, known for its innovation and customer-centric approach. The company operates in a highly competitive market, positioning itself as a disruptor rather than a stable player. This dynamic environment can inspire a culture that thrives on agility, experimentation, and rapid iteration, making it crucial for the Data Engineer I to adapt quickly and maintain a forward-thinking mentality. Company values may focus on leadership principles such as 'Customer Obsession' and 'Invent and Simplify,' which can greatly influence employees’ methods of problem-solving and collaboration. The Data Engineer will likely work as part of a larger cross-functional team, gaining significant visibility into operations and potentially influencing strategic decisions regarding how payment data is managed. This role aligns with Amazon’s broader goals of enhancing customer experience through technology, as it directly impacts the payment acceptance strategies that ensure smooth transactions for buyers and sellers alike.

Absolutely. Here are some mock interview questions that could come up:

• Tell me about a time when you had to solve a complex data architecture problem. How did you approach it?
• Can you describe a project where you implemented data ingestion routines? What challenges did you face?
• Give an example of how you've collaborated with cross-functional teams in your previous roles.
• Describe a situation where you had to translate business requirements into a technical solution. What steps did you take?
• How would you approach building an ETL pipeline for a new data source? Can you outline your methodology?
• What big data technologies have you worked with, and how have you applied them in your past projects?
• If presented with a dataset that has inconsistent formats, what specific steps would you take to standardize it?
• Imagine you have to design a solution for gathering high-frequency transaction data. What considerations would you have in terms of data modeling?
• Why are you interested in working at Amazon, particularly in the Payment Acceptance & Experience team?
• How do you think your values align with Amazon's emphasis on customer obsession and innovation?
• What aspects of working in a fast-paced, technology-driven environment excite you the most?
• What measures do you think are important for ensuring the data solutions you develop are scalable and maintainable?
• Can you describe any experience you have with AWS technologies and how you've used them in past roles?
• What does 'success' in the Data Engineer I role look like to you, and how do you plan to achieve it?
• Are there any specific tools or technologies you're particularly interested in learning more about in this role?