채용
Required Skills
Data Engineering
SQL
Data Modeling
ETL
Do you have the technical chops to build BI solutions that process billions of rows a day using AWS technologies? Do you want to create next-generation tools for intuitive data access? Do you wake up in the middle of the night with new ideas that will benefit your customers? Are you persistent in bringing your ideas to fruition?
In this role, you will have the opportunity to help shape and deliver on a strategy to build PFS using Amazon’s utility computing web services (Amazon EC2 compute, Amazon S3 storage, Amazon Simple DB/RDS databases, Amazon CloudFront, etc.) . You will partner with accounting and tax stakeholders and will strive to earn their trust. You will work directly with your customers and will constantly innovate on their behalf. You will be a great negotiator and enjoy working with diverse mindsets.
Key job responsibilities
First things first, you know SQL and data modeling like the back of your hand. You need to know data relationships, whether relational, non-relational, streams, json, xml etc. and the best way to deal with these. You have a history of coming up with innovative solutions to complex technical problems. You are a quick and willing learner of new technologies and have examples to prove your aptitude. You are not tool-centric; you determine what technology works best for the problem at hand and apply it accordingly. You can explain complex concepts to your non-technical customers in simple terms.
In this role you will be responsible for creating finance systems that support Amazon's global footprint. You should insist on the highest standards for quality, maintainability, and performance. The systems we own are responsible for trillions of financial events that would rank among the largest countries in the world by GDP. You will ensure that engineering best practices are followed and that software is designed to be highly-available, dynamically scalable, and resilient to continuity threats.
As a technology leader, you will drive architectural and design choices and invent new features. We have a team culture that encourages innovation with a high level of ownership for the product vision, technical architecture and project delivery. Successful candidates will be high-bandwidth leaders who can cut through the noise, simplify relentlessly, deliver results, and build great customer experience.
A day in the life
Basic Qualifications
- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
Preferred Qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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About Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
Recommend to a Friend
Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0 reports
$108,330
total / year
Base
$43,332
Stock
$54,165
Bonus
$10,833
$75,831
$140,829
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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