Data Engineer, Amazon Prime Video Product Analytics

Amazon Amazon · Big Tech · Seattle, WA · Data Science

Data Engineer II on the Prime Video Product Analytics team, responsible for building and maintaining data infrastructure for out-of-app engagement and full-funnel customer journey analytics. This includes designing data models and ETL pipelines, enhancing AI tooling, and collaborating with Data Scientists on ML use cases.

What you'd actually do

  1. Design, implement, and maintain scalable and reliable data models and ETL pipelines that span the full customer funnel—including the reporting layer for the out-of-app messaging platform and other PV marketing channel infrastructure.
  2. Build and enhance the AI tooling and analytics products to enable self-serve and improved efficiency.
  3. Partner with engineering and dependency teams to define data contracts, ensure upstream data reliability, and proactively manage communication and change coordination for data schema updates.
  4. Collaborate with Business Intelligence Engineers and Data Scientists to deliver clean, structured data for dashboards, reporting, experimentation, full-funnel attribution, and ML use cases.
  5. Monitor pipeline health, resolve job and cluster issues, and improve automation, testing, and observability to increase system resilience.

Skills

Required

  • 3+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • Experience with SQL

Nice to have

  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

What the JD emphasized

  • AI tooling
  • machine learning use cases

Other signals

  • AI-driven solutions
  • machine learning use cases
  • AI tooling