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职位Amazon

Data Engineer - Finance Technology, Finance Technology

Amazon

Data Engineer - Finance Technology, Finance Technology

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

3w ago

必备技能

SQL

AWS

Are you passionate about data? Does the prospect of dealing with massive volumes of data excite you? Do you want to build data engineering solutions that process billions of records a day in a scalable manner using AWS technologies? Do you want to build the next-generation system for intuitive data access?

Amazon's Finance Technology team is seeking truly innovative Data Engineer to join the team that is shaping the future of the finance/accounting systems. Our ideal candidate thrives in a fast-paced environment, relishes working with large transactional volumes and big data, enjoys the challenge of highly complex business contexts (that are typically being defined in real-time) and is a passionate about data and analytics. Amazon has culture of data-driven decision-making, and demands data that is timely, accurate, and actionable, to meet that need you will work with customers, design and develop data solutions that facilitate and influence day to day decision making.

As a Data Engineer, we expect you to have expertise with data warehousing technical components (e.g. Data Modeling, ETL and Reporting), infrastructure (e.g. hardware and software) and their integration. You should have deep understanding of the architecture for enterprise level data warehouse solutions using multiple platforms (RDBMS, Columnar, Cloud). You are expected to have experience with design, creation, management, and business use of large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. You should be enthusiastic about learning new technologies and be able to implement solutions using them to provide new functionality to the users or to scale the existing platform. Having strong analytical skills is a plus. Above all, you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.

Key job responsibilities

Design, implement, and support a platform providing secured access to large datasets
Interface with Tax, Finance and Accounting customers, gathering requirements and delivering end-to-end BI solutions
Model data and metadata to support ad-hoc and pre-built reporting
Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions
Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
Tune application and query performance using profiling tools and SQL
Analyze and solve problems at their root, stepping back to understand the broader context
Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use
Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS services
Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets
Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment

Basic Qualifications

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

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)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually

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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

2.9

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

2.5

职业发展

2.3

管理层

2.1

35%

推荐给朋友

优点

Good pay and compensation

Strong benefits package

Flexible scheduling options

缺点

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

薪资范围

4个数据点

L2

L3

L4

L5

L6

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

面试经验

10次面试

难度

3.7

/ 5

时长

21-35周

录用率

20%

体验

正面 10%

中性 10%

负面 80%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge