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Data Engineer I, LATAM CARPOOL

Amazon

Data Engineer I, LATAM CARPOOL

Amazon

Sao Paulo, SP, BRA

·

On-site

·

Full-time

·

2w ago

The LATAM Data Engineer is a technical contributor responsible for building and maintaining data pipelines, AI-ready data warehouses, and scalable infrastructure that powers GenAI reasoning agents and BI solutions across Amazon's Mexico and Brazil Retail operations. This role combines traditional data engineering with AI agentic frameworks, enabling Retail stakeholders in MX and BR to access accurate, real-time data through both traditional dashboards and conversational AI interfaces.

The team is Amazon LATAM's data and AI center of excellence, serving internal users across Mexico and Brazil. We build the infrastructure that powers our GenAI backend—a general-purpose reasoning engine that connects to any data source and enables rapid deployment of AI solutions.

Key job responsibilities
1.

AI-Ready Data Warehouse Development:

Build and maintain the common metric warehouse that serves as the single source of truth for all GenAI reasoning agents. This ensures every agent consults consistent, accurate data when analyzing business metrics, generating hypotheses, and validating insights.
2.

Data Pipeline Engineering:

Design and implement scalable ETL/ELT pipelines that power both traditional BI and AI solutions:
3.

Reasoning Agent Data Infrastructure:

Enable reasoning agentic solutions by building robust data foundations that support:

  • Document Analysis Workflows Pipelines feeding multi-phase workflows where agents read, analyze, generate hypotheses, and validate against real data
  • Financial Data Integration: P&L account data with historical patterns for automated analysis and hypothesis generation
  • Selection Analysis Data Funnel and discoverability metrics at product and buying-situation granularity for automated decision support

Basic Qualifications

  • 1+ 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)

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

Amazon

Public

Amazon.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