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Business Intelligence Engineer, Last Mile Analytics

Amazon - Hyderabad, Telangana, IND

Posted May 4, 2026

Benefits

Parental leave
6 weeks From the posting source checked Jun 20, 2026
Non-birth-parent leave
6 weeks From the posting source checked Jun 20, 2026
Family-building benefits
  • Fertility benefits: Offered From the posting source checked Jun 20, 2026
  • Adoption assistance: Offered From the posting source checked Jun 20, 2026
  • Surrogacy assistance: Not verified
Mental health support
Offered From the posting source checked Jun 20, 2026
Relocation assistance
Not verified
Childcare support
Offered From the posting source checked Jun 20, 2026
Learning budget
Not verified
Verification
Source-linked checked Jun 7, 2026
Salary
Not verified
401(k) match
Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Data From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
Not verified

Company

Company stage
Public-company From the posting source checked Jun 20, 2026
Equity
Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter
Not verified
Assessment
Not verified
Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Business Intelligence Engineer, Last Mile Analytics Hyderabad, Telangana, IND When you attract people who have the DNA of pioneers and the DNA of explorers, you build a company of like-minded people who want to invent. And that's what they think about when they get up in the morning: how are we going to work backwards from customers and build a great service or a great product” - Jeff Bezos Amazon.com's success is built on a foundation of customer obsession. Have you ever thought about what it takes to successfully deliver millions of packages to Amazon customers seamlessly every day like a clock work? In order to make that happen, behind those millions of packages, billions of decision gets made by machines and humans. What is the accuracy of customer provided address? Do we know exact location of the address on Map? Is there a safe place? Can we make unattended delivery? Would signature be required? If the address is commercial property? Do we know open business hours of the address? What if customer is not home? Is there an alternate delivery address? Does customer have any special preference? What are other addresses that also have packages to be delivered on the same day? Are we optimizing delivery associate's route? Does delivery associate know locality well enough? Is there an access code to get inside building? And the list simply goes on. At the core of all of it lies quality of underlying data that can help make those decisions in

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