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Data Engineer, AppStar Data Analytics & Engineering

Amazon

Data Engineer, AppStar Data Analytics & Engineering

Amazon

New York, NY, USA

·

On-site

·

Full-time

·

4w ago

必备技能

Python

SQL

AWS

Airflow

Are you passionate about building data infrastructure that powers security insights and analytics at scale? Do you want to contribute to the modernization of a security data platform that enables measurable improvements in application security across Amazon?

As a Data Engineer on the App Star DNA team (Data & Analytics Engineering), you will build and maintain data pipelines and infrastructure that support the App Star organization. You will work across multiple data domains to develop the data infrastructure that powers analytics and reporting.

You should be a builder who is passionate about data engineering and eager to learn. You thrive in solving technical problems, building reliable data pipelines, and contributing to a high-performing team. You bring solid expertise in data modeling, ETL/ELT pipeline design, and distributed data systems, and you're excited to grow your skills in modern data architectures and AWS technologies.

Amazon is continuously innovating new services and features for our customers. Our engineers invent, build, and sometimes break things to make them easier, faster, better, and more cost-effective. However, no matter what we're building—from websites to web services, AR to AI, drones to devices—security is always our top priority. The Amazon Application Security team focuses on working with our builders to provide experiences that our customers can trust. That means constantly learning new things and solving complex problems to protect the safety, security, and privacy of billions of lives on a global scale.

At Amazon, you'll be working with the best minds in technology and security. Learn and be curious here, and accelerate your career growth. You can take pride in knowing that your work is meaningful, having a positive impact on others and making the world a better place.

  • Key job responsibilities
  • Design and implement ETL/ELT pipelines using SQL, Python, and AWS services (Redshift, Glue, S3, Lambda, Step Functions, Athena, Apache Airflow)
  • Build and maintain data models, conformed dimensions, and entity models that support downstream consumption
  • Contribute to the migration and modernization of legacy security data pipelines to modern lakehouse patterns (Apache Iceberg, Spectrum, Lake Formation)
  • Ensure data quality, lineage, and freshness in data pipelines
  • Follow data engineering best practices: data modeling standards, naming conventions, data quality frameworks, CI/CD for data pipelines, and operational excellence
  • Identify and resolve data pipeline issues—simplify complex data flows, remove bottlenecks, and address technical debt
  • Collaborate with senior engineers, business intelligence engineers, data scientists, and security stakeholders to deliver scalable data solutions
  • Design, implement, and support platforms providing secured access to large datasets
  • Analyze and solve problems at their root, stepping back to understand the broader context
  • Learn and understand a broad range of Amazon's security data resources and know when, how, and which to use
  • Continually improve data infrastructure and pipelines, automating or simplifying self-service support for datasets
  • Participate in design reviews, on-call rotations, and incident response for production data pipelines

About the team

Why Amazon Security:

At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon's products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.

App Star DNA Team (Data & Analytics Engineering)
The App Star DNA team supports the App Star organization, which is responsible for securing applications at Amazon. Our team is committed to building world-class data infrastructure that provides the foundation for analytics solutions, enabling visibility into security performance and driving data-informed decision-making across security teams. We work with massive volumes of security data to deliver the infrastructure that powers insights with immediate influence on how Amazon secures its applications and protects customer trust.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.

Inclusive Team Culture:

In Amazon Security, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.

Training and Career Growth:

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.

Basic Qualifications

  • 3+ years of data engineering experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle 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)

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, NY, New York - 145,300.00 - 196,600.00 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