Il y a 8 joursAmazon

Data Engineer

  • City of London (Greater London)
  • Développement informatique

Description de l'offre


Our members love entertainment. Amazon's Prime Video service launched in 2014 and has quickly become a strategic priority for the organization, reflected in the service's recent expansion into over 200 countries and territories around the world. Amazon invests on acquiring, producing and programming TV shows & movies – from brand new, including must-see exclusive series like The Grand Tour, Neil Gaiman's American Gods, to The Man in the High Castle, Transparent, Mr Robot and more.”

In Prime Video, the Subscriptions and Commerce team is responsible for the Amazon customer experience in purchasing and subscribing to video content, from surfacing the most relevant offers and ensuring transactions succeed to handling the lifecycle of everything they have bought.

Amazon sells millions of digital items through its websites and connected devices program. In order to evaluate the performance of the business and make the best forward looking decisions, we need to store and analyze huge sets of data related to subscription, purchase and consumption of digital content.

The Amazon Video Subscription and Commerece Platform (AVCP) team presents exciting opportunities to work on very large data sets in one of the world's largest and most complex data warehouse environments. Our data warehouse is built on AWS cloud technology like Redshift, performing ETL processing on multi terabyte of relational data in a matter of hours. Our team is serious about great design and redefining best practices with a cloud-based approach to scalability and automation.

As a data engineer in this team, you will solve big data warehousing problems on a massive scale. You will apply cloud-based AWS services to solve challenging problems around: big data processing, data warehouse design, and self-service data access. You will be part of a data engineering team that focuses on automation and optimization for all areas of DW/ETL maintenance and deployment.

You will work closely with the business and technical 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 and persist using efficient technologies that can scale to seasonal spikes and deep. Your work will have a direct impact on the day-to-day decision making in the Amazon Video team.
Each day, we process hundreds of billions of rows and 10s of petabytes of data, using our custom-built, high-performance data processing engines. Data is served to hundreds of internal customers.The demand for analytics and data-freshness, coupled with our sheer volume of data and performance requirements, means that we have moved well beyond any industry-leading standard offerings.

So if you think Hadoop is slow; You perceive 100s of terabytes to be small, then we have a position for you.We are looking for a person who thrives on big challenges! A person who is not afraid of thinking big and challenging the status quo. Ideally you have a proven track-record of building high-performance, high-availability database technology. In addition you have a passion for code and design, and providing technical leadership and mentoring.

Profil recherché


· Bachelor's Degree in Computer Science or a related technical discipline.
· Experience writing high quality, maintainable SQL on large datasets.
· Ability to write code in Python, Ruby, Scala or other platform related Big data technology.
· Expertise in Star Schema data modelling
· Experience working in an Agile environment
· Exposure/Experience in Bigdata Technologies (hadoop, spark, presto, etc.).
· Experience in Datawarehousing and Analytics domain building large scale solutions
· Strong analytical and problem solving skills
· Expertise in the design, creation and management of large datasets/data models
· Experience working on building /optimizing logical data model and data pipelines while delivering high data quality solutions that are testable and adhers to SLAs
· Experience in using various data design patterns and knows when/when not to use one
· Excellent verbal and written communication skills
· Ability to work with business owners to define key business requirements and convert to technical specifications