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Data Engineer II, Amazon Payment Products

Amazon

Data Engineer II, Amazon Payment Products

Amazon

Bengaluru, KA, IND

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

401(k) matching

Generous paid time off and holidays

Comprehensive health, dental, and vision insurance

Competitive salary and equity package

Healthcare

Equity

Required Skills

PostgreSQL

Python

Node.js

Amazon is seeking a talented Data Engineer II to join our team. In this role, you will design, build, and optimize data infrastructure that enables data-driven decision making across the organization. You'll work autonomously on complex data challenges while collaborating with cross-functional teams to deliver high-quality data solutions.
Key job responsibilities
Design, build, and optimize logical data models and data pipelines for complex datasets
Own ongoing data quality and create self-service access to datasets for business intelligence
Work on major portions of existing or new data architecture within the team
Collaborate with Software Development Engineers and other Data Engineers to design stable, performant data solutions
Write secure, stable, testable, and maintainable code with minimal defects
Apply appropriate data design approaches and make judicious trade-offs without over-engineering
Optimize resource usage including system hardware, data storage, query optimization, and AWS infrastructure
Participate actively in code reviews, design discussions, and team planning
Mentor and train junior team members and new peers
Resolve root causes of complex problems and balance customer requirements with team needs
Stay current on distributed systems technologies (Map Reduce, MPP architectures, NoSQL databases)
A day in the life
As a DE II, you'll leverage your expertise in distributed systems and data technologies to solve difficult problems and contribute meaningfully to the team's data architecture while maintaining high standards of operational excellence.

Basic Qualifications

  • 3+ years of data engineering experience
  • 4+ years of SQL experience
  • Experience with data modeling, warehousing and building ETL pipelines

Preferred Qualifications

  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
  • Experience building data pipelines and ETL processes for large language models (LLMs) and generative AI applications
  • Knowledge of vector databases and embeddings for semantic search and GenAI applications
    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