Data Engineer, Video Content Researcher
4 weeks ago
As a Data Engineer on the Prime Video team, you will design, implement, and support scalable data infrastructure solutions to integrate with multi-heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, machine learning models, and ad-hoc data requests.
You will work closely with Product Managers, Applied Scientists, and Economists to explore new data sources and build pipelines for same that expands existing ML models.
The mission of the Video Content Research team is to provide analytics and science to support customer-driven content decisions. We are product-focused, so we build reliable, scalable, worldwide tools.
We measure the long-run economic value of Prime Video, and we help define the strategies and support decisions to maximize this value.
Key Responsibilities:
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL/python and AWS big data technologies such as EMR, Redshift.
- Designing and implementing complex ETL pipelines by processing petabytes of data that empowers scientists in team to build large-scale Machine Learning models.
- Work closely with Product Managers, Applied Scientists, and Economists in team to explore new data sources and build pipelines for same that expands existing ML models.
About the Team:
Our team predicts how many customers will watch any new show that Amazon Studios is considering creating. We build complex data products to provide insights into customer segments worldwide and support scaled forecasting tools.
We measure and forecast the performance of our marketing campaigns, and how many new customers will our advertising spend drive.
We collect diverse signals of marketing impressions and publish model outputs for driving key business decisions.
We analyze key metrics that attract new Prime members. We build tools that measure the long-run value driven by customer engagement with our content.
Requirements:
- 4+ years of data engineering experience
- Experience with data modeling, warehousing, and building ETL pipelines
- Experience with SQL
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
Preferred Qualifications:
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
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