Jobs
Benefits & Perks
•Mentorship & Career Growth
•Work/Life Balance
•Learning Budget
•Learning
Required Skills
Data engineering
Data modeling
Data warehousing
ETL
SQL
Python
- Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience
- Amazon continues to grow and evolve as a world-class e-commerce platform.
The competitive pricing team is responsible for ensuring that we earn and keep our customer trust around our low prices. This involves ensuring for all the products that are sold on Amazon marketplaces worldwide, customers get the best price. Data engineering team - a part of pricing Big Data team - is responsible for building and maintaining the data platform that helps Amazon businesses worldwide in maintaining price competitiveness. By collating and transforming large amount of data from various sources, exposing pricing gaps via dashboards and reports and providing ability to deep dive and extract insights, data engineering team helps in improving operational efficiency and meeting business goals around pricing.
You will be part of team that will work with the tech, analytics, product, machine learning and technology teams to provide real time data processing solution that give Amazon leadership, PMs timely, flexible and structured access to customer insights. The team will be responsible for building this platform end to end using latest AWS technologies and software development principles.
As a Data Engineer , you will be responsible for leading the architecture, design and development of the data, metrics and reporting platform for Pricing. You will architect and implement new and automated Business Intelligence solutions, including big data and new analytical capabilities that support our Development Engineers, Analysts and Retail business stakeholders with timely, actionable data, metrics and reports while satisfying scalability, reliability, accuracy, performance and budget goals and driving automation and operational efficiencies. You will partner with business leaders to drive strategy and prioritize projects and feature sets. You will also write and review business cases and drive the development process from design to release. In addition, you will provide technical leadership and mentoring for a team of highly capable Data Engineers.
Key job responsibilities
- Own design and execution of end to end projects
- Own managing Amazon Pricing services data infrastructure
Build end to end Data Pipeline for Amazon Pricing:
- Establish key relationships which span Amazon business units and Business Intelligence teams
- Implement standardized, automated operational and quality control processes to deliver accurate and timely data and reporting to meet or exceed SLAs
Basic Qualifications
- 2+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, Korn Shell)
- Bachelor's degree or above in computer science, computer engineering, or related field
Preferred Qualifications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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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