招聘
Are you passionate about building data-driven solutions to drive the profitability of the business? Are you excited about solving complex real world problems? Do you have proven analytical capabilities, exceptional communication, project management skills, and the ability to multi-task and thrive in a fast-paced environment? Join us a Business Intelligence Engineer to deliver analytics solutions for Amazon Payment Products.
Amazon Payment Products team creates and manages a global portfolio of products, including co-branded credit cards, instalment financing, third party redemptions, etc. Within this team, we are looking for a Business Intelligence Engineer responsible for performing analysis on large volumes of data which includes building data pipelines, dashboards, synthesizing the analysis into business insights and communicating the findings to various stakeholders. To be eligible, the candidate must possess superior written and verbal communication skills too, in addition to proven analytical skills.
- Key job responsibilities
- Identify, develop and execute data analysis to uncover areas of business opportunity
- Learn and understand a broad range of Amazon’s data resources and know how, when and which data sources to use
- Deep dive into massive data sets, build data pipelines using SQL, dashboards using Quick Sight, data self-service using Generative/Agentic AI products like Quick Suite
- Present insights and recommendations to key stakeholders in both verbal and written form
- Manage and execute entire project from start to finish including problem solving, data gathering and manipulation, predictive modeling and project management
Basic Qualifications
- Undergraduate degree in mathematics, engineering, statistics, computer science, business administration or a related field
- At least 5 years of experience using SQL to build data pipelines and dashboards like Quick Sight
- Strong Analytical skills – has ability to start from ambiguous problem statements, identify and access relevant data, make appropriate assumptions, perform insightful analysis and draw conclusion relevant to the business problem
- Communication skills – Demonstrated ability to communicate complex technical problems in simple plain stories. Ability to present information professionally & concisely with supporting data.
- Experience in building Generative/Agentic AI solutions to drive internal productivity of the team and productivity of stakeholder team by enabling data self-service
- Ability to work in a fast-paced business environment and demonstrated track record of project delivery for large, cross-functional projects with evolving requirements
Preferred Qualifications
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Master's degree in Operations Research, Statistics, Applied Mathematics, Engineering, Computer Science or related field
- Experience in building predictive models, optimization models using Python to make business decisions
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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