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Data Engineer, Project Accounting

职能数据工程
级别中级
地点Hyderabad, TS, India
方式现场办公
类型全职
发布1个月前
立即申请

Do you have the technical chops to build BI solutions that process billions of rows a day using AWS technologies? Do you want to create next-generation tools for intuitive data access? Do you wake up in the middle of the night with new ideas that will benefit your customers? Are you persistent in bringing your ideas to fruition?

In this role, you will have the opportunity to help shape and deliver on a strategy to build PFS using Amazon’s utility computing web services (Amazon EC2 compute, Amazon S3 storage, Amazon Simple DB/RDS databases, Amazon CloudFront, etc.) . You will partner with accounting and tax stakeholders and will strive to earn their trust. You will work directly with your customers and will constantly innovate on their behalf. You will be a great negotiator and enjoy working with diverse mindsets.

Key job responsibilities
First things first, you know SQL and data modeling like the back of your hand. You need to know data relationships, whether relational, non-relational, streams, json, xml etc. and the best way to deal with these. You have a history of coming up with innovative solutions to complex technical problems. You are a quick and willing learner of new technologies and have examples to prove your aptitude. You are not tool-centric; you determine what technology works best for the problem at hand and apply it accordingly. You can explain complex concepts to your non-technical customers in simple terms.

In this role you will be responsible for creating finance systems that support Amazon's global footprint. You should insist on the highest standards for quality, maintainability, and performance. The systems we own are responsible for trillions of financial events that would rank among the largest countries in the world by GDP. You will ensure that engineering best practices are followed and that software is designed to be highly-available, dynamically scalable, and resilient to continuity threats.

As a technology leader, you will drive architectural and design choices and invent new features. We have a team culture that encourages innovation with a high level of ownership for the product vision, technical architecture and project delivery. Successful candidates will be high-bandwidth leaders who can cut through the noise, simplify relentlessly, deliver results, and build great customer experience.

A day in the life

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)

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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关于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+

员工数

Seattle

总部位置

$1.5T

企业估值

评价

10条评价

3.4

10条评价

工作生活平衡

2.5

薪酬

4.2

企业文化

3.0

职业发展

3.8

管理层

2.7

65%

推荐率

优点

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

缺点

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

薪资范围

4个数据点

L2

L6

L3

L4

L5

L2 · Data Analyst L2

0份报告

$108,330

年薪总额

基本工资

$43,332

股票

$54,165

奖金

$10,833

$75,831

$140,829

面试评价

6条评价

难度

4.0

/ 5

时长

21-35周

体验

正面 0%

中性 17%

负面 83%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge