Jobs
Amazon Extra Large (AMXL) is looking for a customer focused, analytically and technically skilled Business Intelligence Engineer to drive effective performance measurement and management, innovation and execution in last mile delivery. This position will be responsible for building out analysis and visualization tools and processes’ to support our growing Amazon Logistics business in Europe.
The successful candidate will be able to effectively retrieve, integrate, visualize and present critical data to improve the efficiency of the package delivery network, and enable efficient management of a large global logistics system. This individual will work with technical and business teams to optimize planning, execution, process improvement and track progress against goals. This role requires an individual with excellent analytical abilities as well as outstanding business acumen and comfort with technical teams and systems. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and enjoy working with large scale of data.
- Key job responsibilities
- Maintain and develop data pipeline for EU region
- Automate and improve existing manual processes
- Create tools to help deep diving and investigations into operations execution and business problems
- Analyze and visualize large scale logistics and transaction data to determine user behavior or delivery process problems, and output solid analysis report with recommendation.
Basic Qualifications
- Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, Quick Sight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
- Experience with SQL
- Experience in the data/BI space
Preferred Qualifications
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
m/w/d
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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