Data Engineer, Prime Video - GSS Planning & Strategy

Requirements

• Bachelor's degree in business, engineering, statistics, computer science, mathematics or a related field
• 3+ years of data engineering experience
• 3+ years of experience 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 (e.g., SQL, PL/SQL, DDL, HiveQL, SparkSQL, Scala).
• Experience with Python or another scripting language for data processing.
• Knowledge of data schema design including normalization, relational models, and dimensional models.
• Cross-team collaboration skills and effective written and verbal communication when interfacing with stakeholders, peers, and executives.
• Knowledge of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews, source control, continuous deploymen

Additional Information

Prime Video offers customers a vast collection of movies, series, and sports-all available to watch on hundreds of compatible devices. U.S. Prime members can also subscribe to 100+ channels including Max, discovery+, Paramount+ with SHOWTIME, BET+, MGM+, ViX+, PBS KIDS, NBA League Pass, MLB.TV, and STARZ with no extra apps to download, and no cable required. Prime Video is just one of the savings, convenience, and entertainment benefits included in a Prime membership. More than 200 million Prime members in 25 countries around the world enjoy access to Amazon's enormous selection, exceptional value, and fast delivery. Are you interested in shaping the future of entertainment? Prime Video's technology, marketing, and operations teams are creating the best-in-class digital video experience. You'll get to work on projects that are fast-paced, challenging, and varied. You'll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. Within our Prime Video Global Operations team, we're looking for a results-driven Data Engineer to build and scale the data infrastructure backbone that powers our reporting, analytics, and AI-enabled insights capabilities. In this role, you will design and implement robust data pipelines, integrate data from marketing, business teams, finance, and cross-functional teams. You will also build AI/ML-enabled data solutions and architect the foundational data infrastructure that enables insights, planning, reporting mechanisms, and agentic AI-powered self-service analytics for Amazon PV Global Operations. This individual has deep expertise in data engineering - including scalable ETL/ELT pipelines, data modeling, and architecting solutions that support high-impact business intelligence. You will be responsible for strengthening Prime Video's Global Marketing Operations data infrastructure, operational metrics pipelines, and capacity planning data systems. You will build automated, reliable, and performant data solutions that translate enterprise strategy into actionable forecasting, planning, and delivery frameworks. Your work will directly influence data-driven business decisions that result in quantifiable outcomes. The ideal candidate has a strong sense of ownership, is self-driven, and loves to solve complex data challenges at scale. You will bring a mix of experience including data pipeline development, data modeling and governance, infrastructure automation, stakeholder collaboration, and process optimization, with a forward-looking mindset toward AI enablement. If you enjoy building the engineering foundation that powers next-generation analytics, working in a fast-paced dynamic environment, and being challenged by new problems, we'd like to speak with you! Key job responsibilities * Design, develop, and maintain scalable, automated data pipelines and ETL/ELT processes that ingest, transform, and deliver data to support business reporting and analytics needs. * Architect data infrastructure for agentic AI and Model Context Protocols (MCP) - including structured pipelines, usage data capture, and systems that power AI-enabled self-service analytics and reporting. * Build and maintain data lakes, data warehouses, and APIs ensuring reliable, performant access to clean, well-governed data. Optimize storage, queries, and AWS infrastructure costs. * Create logical data models that drive physical design, enabling BI/analytics teams to build self-service reporting on a solid foundation. Support forecasting and capacity planning at scale. * Establish data quality frameworks, monitoring, and alerting to ensure accuracy, completeness, and freshness. Drive governance best practices including lineage tracking, 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.

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