Data Engineer, Prime Video - GSS Planning & Strategy

Amazon's Prime Video Global Operations is seeking a Data Engineer to design and scale data infrastructure, pipelines, and AI-enabled analytics that empower marketing, finance, and cross-functional teams. This onsite role in Seattle, WA offers a salary range of USD 132,100 to 178,800 per year and requires a bachelor’s degree along with a minimum of three years of data engineering experience. The position centers on building robust data solutions that drive critical business insights and operational decisions.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes to ingest, transform, and deliver data for reporting and analytics needs.
• Architect data infrastructure for agentic AI and Model Context Protocols (MCP), including structured pipelines, usage data capture, and systems supporting AI-enabled self-service analytics and reporting.
• Build and maintain data lakes, data warehouses, and APIs to ensure reliable, performant access to clean, governed data; optimize storage, query performance, and AWS infrastructure costs.
• Create logical data models that drive physical design, enabling BI and analytics teams to build self-service reporting on a solid foundation and support forecasting at scale.
• Establish data quality frameworks, monitoring, and alerting to ensure accuracy, completeness, and freshness; drive governance practices including lineage, documentation, and access controls.
• Own instrumentation strategy for key platforms, ensuring comprehensive data capture across operational workflows.
• Partner cross-functionally with BI engineers, analysts, operations, science, and tech teams to translate data requirements into scalable solutions.

Requirements

• Bachelor’s degree in business, engineering, statistics, computer science, mathematics, or a related field.
• 3+ years of data engineering experience.
• 3+ years working with big data technologies such as Hadoop, Hive, Spark, or EMR.
• Experience with data modeling, warehousing, and building ETL/ELT pipelines.
• 4+ years of experience with one or more query languages (SQL, PL/SQL, DDL, HiveQL, SparkSQL, Scala).
• Experience using Python or another scripting language for data processing.
• Knowledge of data schema design, including normalization, relational models, and dimensional models.
• Strong cross-team collaboration skills and effective written and verbal communication when interfacing with stakeholders, peers, and executives.
• Understanding of professional software engineering practices for the full software development lifecycle, including coding standards, code reviews, version control, continuous deployment, testing, and operational excellence.
• Experience using BI tools (e.g., Tableau, QuickSight) to visualize data.

Technologies

• Hadoop
• Hive
• Spark
• EMR
• SQL
• PL/SQL
• DDL
• HiveQL
• SparkSQL
• Scala
• Python
• Tableau
• QuickSight
• S3
• Redshift
• SageMaker
• 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 architecting and operating solutions built on AWS services including S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2.
• Experience in large-scale workforce, operations, or capacity planning functions.
• Experience in data mining and handling large and complex datasets in a business context.
• Experience in statistical analysis using tools such as R, SAS, or Matlab.