招聘
Are you passionate about data and code? Does the prospect of dealing with mission-critical data excite you? Do you want to build data engineering solutions that process a broad range of business and customer data? Do you want to continuously improve the systems that enable annual worldwide revenue of hundreds of billions of dollars? If so, then the e Commerce Services (eCS) team is for you!
In e Commerce Services (eCS), we build systems that span the full range of e Commerce functionality, from Privacy, Identity, Purchase Experience and Ordering to Shipping, Tax and Financial integration. e Commerce Services manages several aspects of the customer life cycle, starting from account creation and sign in, to placing items in the shopping cart, proceeding through checkout, order processing, managing order history and post-fulfillment actions such as refunds and tax invoices. eCS services determine sales tax and shipping charges, and we ensure the privacy of our customers. Our mission is to provide a commerce foundation that accelerates business innovation and delivers a secure, available, performant, and reliable shopping experience to Amazon’s customers.
The goal of the eCS Data Engineering and Analytics team is to provide high quality, on-time reports to Amazon business teams, enabling them to expand globally at scale. Our team has a direct impact on retail CX, a key component that runs our Amazon fly wheel.
As a Data Engineer, you will own the architecture of DW solutions for the Enterprise using multiple platforms. You would have the opportunity to lead the design, creation and management of extremely large datasets working backwards from business use cases. You will use your strong business and communication skills to be able to work with business analysts and engineers to determine how best to design the data warehouse for reporting and analytics. You will be responsible for designing and implementing scalable ETL processes in the data warehouse platform to support the rapidly growing and dynamic business demand for data and use it to deliver the data as service which will have an immediate influence on day-to-day decision making.
- Key job responsibilities
- Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal BDT tools (Data Net, Cradle, Quick Sight etc.
- Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.
- Develop new data models and end to data pipelines.
- Create and implement Data Governance strategy for mitigating privacy and security risks.
Basic Qualifications
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- 5+ years of data engineering experience
- Bachelor's degree
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%
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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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