招聘
We are seeking a highly skilled Data Engineer to join our Fin Tech ADA team, responsible for building and optimizing scalable data pipelines and platforms that power analytics, automation, and decision-making across Finance and Accounting domains. The ideal candidate will have strong expertise in AWS cloud technologies including Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM, along with hands-on experience designing secure, efficient, and resilient data architectures.
You will work with large-scale structured and unstructured datasets, leveraging both relational and non-relational data stores (object storage, key-value/document databases, graph, and column-family stores) to deliver reliable, high-performance data solutions. This role requires strong problem-solving skills, attention to detail, and the ability to collaborate with cross-functional teams to translate business needs into technical data solutions.
Key job responsibilities
Scope -
Fintech is seeking a Data Engineer to be part of Accounting and Data Analytics team. Our team builds and maintains data platform for sourcing, merging and transforming financial datasets to extract business insights, improve controllership and support financial month-end close periods. As a contributor to a crucial project, you will focus on building scalable data pipelines, optimizations of existing pipelines and operation excellence.
- Qualifications-
- 5+ yrs experience as Data Engineer or in a similar role
- Experience with data modeling, data warehousing, and building ETL pipelines
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Extensive experience working with AWS with a strong understanding of Redshift, EMR, Athena, Aurora, DynamoDB, Kinesis, Lambda, S3, EC2, etc.
- Experience with coding languages like Python/Java/Scala
- Experience in maintaining data warehouse systems and working on large scale data transformation using EMR, Hadoop, Hive, or other Big Data technologies
- Experience mentoring and managing other Data Engineers, ensuring data engineering best practices are being followed
- Experience with hardware provisioning, forecasting hardware usage, and managing to a budget.
- Exposure to large databases, BI applications, data quality and performance tuning
Basic Qualifications
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
Preferred Qualifications
- 5+ years of data engineering experience
- 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
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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