Senior Data Engineer, Prime Video APAC and ANZ Analytics Team

Are you interested in shaping the future of entertainment? Prime Video's technology, marketing, and operations teams are creating the best-in-class digital video experience. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. Prime Video APAC and ANZ team is seeking a curious, resourceful, and experienced Data Engineer to develop a scalable data warehouse architecture and performant data models that powers our analytical ecosystem and day-to-day decision making. The team presents an exciting opportunity to work on very large data sets in one of the world's largest data warehouse environments. Our data warehouse is built on AWS cloud technologies such as Spectrum and Redshift for performing ETL processing of TBs of relational data. As a Senior Data Engineer in this team, you will solve big data warehousing problems on a large scale. You will apply cloud-based AWS services to solve challenging problems around: big data processing, data warehouse design, and enabling self-service. You will focus on automation and optimization for all areas of DW/ETL maintenance and deployment. You will work closely with our business intelligence engineers, data scientists as well as marketing and content acquisition teams on many non-standard and unique business problems and use creative problem solving to deliver actionable output. The role of data engineer in Amazon requires excellent technical skills in order to develop systems and tools to process data as well as, but not limited to, the ability to analyze data. Your work will have a direct impact on the day-to-day decision making in the Prime Video team. The successful candidate will be a self-starter who is comfortable with ambiguity and large data sets. They will have strong attention to detail and an ability to work in a fast-paced and entrepreneurial environment.

Basic qualifications

• 3+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience mentoring team members on best practices
• Ability to write high quality, maintainable, and robust code (often in SQL)

Preferred qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience operating large data warehouses