Data Engineer
DESCRIPTION
Want to participate in building the next generation of online payment system that supports multiple countries and payment methods?
Amazon Payment Services (APS) is a leading payment service provider in MENA region with operations spanning across 8 countries and offers online payment services to thousands of merchants. APS team is building robust payment solution for driving the best payment experience on & off Amazon.
Over 100 million customers send tens of billions of dollars moving at light-speed through our systems annually. We build systems that process payments at an unprecedented scale with accuracy, speed and mission-critical availability. We innovate to improve customer experience, with support for currency of choice, in-store payments, pay on delivery, credit and debit card payments, seller disbursements and gift cards. Many new exciting & challenging ideas are in the works.
A day in the life
Data Engineers focus on managing data requests, maintaining operational excellence, and enhancing core infrastructure. You will be collaborating closely with both technical and non-technical teams to design and execute roadmaps
Key job responsibilities
Responsibilities
Data Analysis: Understand business processes, logical data models, relational database implementations, build data driven insights to improve payment processing
Reviews:Perform Code/design reviews and offer feedback on design, integration, performance and scalability issues.
Manage data infrastructure
Hands-on experience designing, developing, and maintaining data pipelines and
data integration solutions.
BASIC QUALIFICATIONS
- 7+ 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
PREFERRED QUALIFICATIONS
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
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