招聘
We're seeking an experienced Data Engineering Manager to build data & analytics platform for Risk and Compliance Solutions (RCS) products. RCS serves as a crucial safeguard for Amazon's buyers, brands, and selling partners while ensuring business teams meet their regulatory obligations. Operating under the Three Lines of Defense (3LoD) model, RCS functions as the second line of defense, providing specialized oversight, monitoring, and expertise while setting policies and procedures that guide Amazon's compliance framework. RCS's mission is to leverage specialist industry insights and Amazon's unique way to scale through technology, delighting customers through tailored compliance solutions.
RCS's work spans multiple critical areas, including enabling Amazon's financial services expansion through streamlined license acquisition, managing existing business risks, delivering comprehensive governance, risk, and assurance services across Amazon, developing innovative solutions like Compliance as a Service (CaaS) and transforming compliance operations into a proactive, intelligence-led framework.
This role is critical for RCS's mission to scale compliance operations through technology, reduce manual processes, and enable Amazon's global expansion while maintaining regulatory compliance. The role sits in the sweet spot between technology and business worlds and provides opportunities for learning, growth, high business impact, and working with seasoned global business leaders.
The ideal candidate will be an analytical, results-oriented, self-motivated, and customer-focused engineering leader who will play a key role in continuous improvement for the critical systems that enable our entire RCS business.
An ideal candidate will be someone with sound technical background in data domain (storage, processing, and analytics), has solid business acumen, and has strong automation solution-oriented thought process. Will be a self-starter who can start with a business problem and work backwards to conceive and formulate best possible solution. Is a great communicator and at ease on partnering with business owners and all other stakeholders. Can explore newer technology options as needed, and has a high sense of ownership over every deliverable by the team. Is constantly obsessed with customer delight and business impacting end result(s) and ‘gets it done’ in business time.
- Key job responsibilities
- Architect and implement a scalable, cost-optimized S3-based Data Lake for RCS that unifies structured and unstructured data from disparate sources.
- Architect and implement a scalable, cost-performance-optimized OLAP-based analytics layer
- Establish metadata management with automated data classification and lineage tracking.
- Architect a centralized metrics repository that becomes the source of truth for all metrics, reports, and dashboards.
- Implement robust data quality frameworks with staging-first policies and automated validation pipelines.
- Design extensible metrics schemas that support complex analytical queries while optimizing for AI retrieval patterns.
- Establish automated compliance validation frameworks ensuring data handling meets Amazon's security standards.
- Architect and implement scalable, reliable data pipelines and infrastructure, supporting analytics at scale
- Design and enforce data modeling standards, lineage, and governance frameworks while ensuring secure, compliant solutions
- Lead technical design/code reviews, evaluate emerging technologies, and drive engineering best practices across development lifecycle
- Mentor engineers, foster technical excellence, and empower team self-service capabilities for handling complex data tasks independently
- Collaborate with a cross functional global team of product managers, engineers, and stakeholders.
- Drive OP1, OP2, WTR, Sprints, MTR, Roadmap prioritizations, and QTR for the RCS data and analytics Team.
A day in the life
Data Engineering Manager in this role is responsible for architecting, and delivering analytics solutions that will highly impact risk and compliance services team worldwide to provide excellent service and support to Amazon Businesses. This Data Engineering Manager will meet regularly with representatives from product and engineering teams to gather data and analytics requirements, transform complex requirements into seamless analytics presentations, collaborate with global stakeholders, and represent the data and analytics team in all appropriate forums.
Basic Qualifications
- 5+ years of data engineering experience
- Experience managing a data or BI team
- 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience
- Experience communicating to senior management and customers verbally and in writing
- Experience leading and influencing the data or BI strategy of your team or organization
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- 2+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience
- 2+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience
Preferred Qualifications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with AWS Tools and Technologies (Redshift, S3, EC2)
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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