Data Engineer, Prime Video - GSS Planning & Strategy

Join Prime Video Global Operations as a Data Engineer responsible for designing scalable data ecosystems, pipelines, and AI-enabled analytics across marketing, finance, and cross-functional teams.

Responsibilities

• Create and sustain scalable data pipelines and ETL or ELT workflows to ingest, transform, and deliver data for reporting and analytics needs.
• Architect data foundations to support agentic AI and Model Context Protocols (MCP), including structured pipelines, usage data capture, and systems enabling AI-powered self-service analytics and reporting.
• Develop and maintain data lakes, data warehouses, and APIs to ensure reliable, fast access to clean, governed data; optimize storage, query performance, and AWS cost efficiency.
• Design logical data models that guide physical implementations, enabling BI and analytics teams to build self-service reporting on a solid foundation; support scalable forecasting and capacity planning.
• Implement data quality programs with monitoring and alerting to ensure accuracy, completeness, and freshness; promote governance practices like lineage, documentation, and access controls.
• Own the instrumentation strategy for key platforms to guarantee comprehensive data capture across operational workflows.
• Collaborate across BI engineers, analysts, operations, science, and software teams to translate data needs into scalable solutions.

Requirements

• Bachelor's degree in a quantitative or technical field such as engineering, statistics, computer science, mathematics, or a related discipline
• Minimum 3 years of data engineering experience
• At least 3 years working with big data technologies such as Hadoop, Hive, Spark, or EMR
• Experience modeling data, building data warehouses, and constructing ETL/ELT pipelines
• 4+ years of experience with one or more query languages (SQL, PL/SQL, DDL, HiveQL, SparkSQL, Scala)
• Proficiency in Python or another scripting language for data processing
• Knowledge of data schema design, including normalization, relational models, and dimensional models
• Strong cross-functional collaboration and clear written and verbal communication with stakeholders, peers, and leaders
• Familiarity with professional software engineering practices across the full SDLC, including coding standards, code reviews, source control, CI/CD, testing, and operational excellence
• Experience using BI tools such as Tableau or QuickSight to visualize data

Technologies

• Hadoop, Hive, Spark, EMR
• SQL, PL/SQL, DDL, HiveQL, SparkSQL, Scala
• Python
• Tableau, QuickSight
• AWS services: S3, Redshift, SageMaker, EMR, Kinesis, Lambda, EC2
• Informatica, Airflow, ODI, SSIS, BODI, Datastage

Benefits

• Health insurance
• 401(k) matching
• Paid time off
• Parental leave

Preferred Qualifications

• Advanced degree (MS) in engineering, technology, statistics, analytics, or finance
• Experience using BI tools (Tableau, QuickSight) to visualize data
• Experience developing, scaling, and governing global operations standards and infrastructure across matrixed organizations
• Experience with ETL tools such as Informatica, Airflow, ODI, SSIS, BODI, or Datastage
• Experience designing and operating solutions on AWS including S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2
• Experience in large-scale workforce, operations, or capacity planning
• Experience data mining and working with large-scale, complex datasets in business settings
• Experience with statistical analysis using R, SAS, or Matlab