招聘
必备技能
Python
Java
SQL
Scala
The Payroll Metrics, Analytics, and Product Team (MAPT) builds the data foundations that power pay accuracy and payroll intelligence for over one million Amazon employees worldwide. Our mission is to transform payroll data into actionable intelligence that drives confident decision-making, ensures perfect pay experiences, and sets the industry standard for workforce analytics excellence. You will have the opportunity to work at the intersection of payroll operations and data engineering, building systems that directly impact every Amazonian's paycheck.
You will be responsible for designing and building scalable data pipelines, automated reporting frameworks, and analytics platforms that surface payroll defect trends, pay processing metrics, and operational health indicators to senior leadership. As a senior data engineer, you'll be a technical leader responsible for architectural decisions, data modeling strategy, and mentoring that shape both our data platforms and team members.
- Key job responsibilities
- You'll define and drive the technical vision for payroll data pipelines, mentor engineers, and drive innovation in how we ingest, process, store, and serve payroll data across the global organization.
- You will lead the design and implementation of enterprise data platforms that support pay defect analytics, payroll processing metrics, and operational dashboards viewed at the highest levels in the organization.
- You'll own data systems that integrate across multiple payroll engines, HR systems, and financial platforms spanning dozens of countries.
- You will architect data quality frameworks, validation rules, and monitoring solutions that ensure accuracy and reliability across all payroll data products.
- You will work closely with payroll operations, finance, and product teams to solve non-standard, complex business problems and deliver actionable, data-driven output.
- You should have deep expertise in the design, creation, management, and business use of large-scale datasets across multiple data domains.
- You will leverage AI and automation to accelerate data product development and improve data quality.
A day in the life
You will be driving architecture decisions on scaling payroll data platforms, designing ETL pipelines that integrate data from global payroll systems, building and refining dashboards and self-service analytics tools, collaborating with BI engineers and analysts on data modeling, partnering with payroll operations teams to define metrics and validation rules, and mentoring team members on engineering best practices. You'll balance hands-on engineering with technical leadership, ensuring our data products are reliable, accurate, and delivered on schedule.
Basic Qualifications
- 6+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
Preferred Qualifications
- Experience operating large data warehouses
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
- Experience in automation or monitoring frameworks, deployment or development
- Experience with AI/ML technologies
- Experience with payroll, HR, or financial data domains
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
PublicAmazon.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
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