Data Engineering Manager, Planning and Audience Insights

About the role

The US Planning & Audience Insights team sits within US Prime Video. We operate across six functions: Business Planning, Product-Tech, Analytics, Data Science, Data Engineering, and Research. Our stakeholders span content programming, content acquisition, marketing, and PV senior leadership. Our 2026 roadmap is anchored in two investment themes (AI Tooling & Automation and Audience Infrastructure & Insights) spanning content optimization, experimentation, marketing, customer journey, marketplace, and competitive intelligence. Our products serve content programmers, marketing strategists, and senior leadership. We build tools that help PV decide what to release, when to release it, who to target, and how to measure success at scale.

Requirements

• 7+ years of data engineering experience
• Experience managing a data or BI team
• 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience
• 3+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience
• Experience leading and influencing the data or BI strategy of your team or organization
• Experience communicating to senior management and customers verbally and in writing
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience with AWS Tools and Technologies (Redshift, S3, EC2)
• Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
• Knowledge of digital creative production, ad serving, cross-channel attribution, and media analytics
• Experience developing cl

Additional Information

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming across thousands of devices, from award-winning Amazon MGM Studios originals to live sports, channels, and TVOD. Behind the content our customers love is a team shaping what gets released, when, and for whom. The US Planning & Audience Insights team is where strategy meets data meets AI: we build the tools and intelligence that power programming decisions, audience growth, and marketing optimizations. We're looking for a Data Engineering Manager to lead the Data Engineering function within Prime Video's US Planning & Audience Insights team. This team defines Prime Video's north star (long-term strategy, priority audiences, and growth objectives) and delivers the customer intelligence, analytics, and AI-powered solutions that enable the organization to achieve them. You'll lead a team of senior data engineers and own the data infrastructure, pipelines, and platform capabilities that power our analytics, AI tools, and business-critical applications. Your team's work directly enables content programming, marketing optimization, and audience strategy for one of the world's largest streaming services. This requires you to balance competing priorities, manage complex stakeholder relationships, and work shoulder-to-shoulder with product managers, data scientists, and analytics to deliver scalable data solutions at pace. Key job responsibilities - Lead and develop a team of senior data engineers, hiring, mentoring, setting technical direction, managing performance and growth opportunities. - Own the data platform strategy and roadmap for the team's portfolio, including multiple Redshift clusters, ETL/ELT pipelines, and data models that serve analytics, data science, and business stakeholders. - Manage and optimize Redshift infrastructure, ensuring performance, cost efficiency, availability, and scalability across multiple clusters serving diverse business lines. - Own data pipelines for AI-powered tools, ensuring reliable, high-quality data flows that power the team's GenAI and ML applications including content analysis, audience segmentation, and experimentation automation. - Drive data engineering for business-critical applications, including dashboards and other internal self developed software products. - Establish and enforce data governance, quality, and reliability standards, implementing monitoring, alerting, SLAs, and data quality frameworks across the team's data assets. - Partner cross-functionally with product managers, data scientists, BI engineers, and software engineers to translate business requirements into scalable data architecture and pipeline solutions. - Represent data engineering in planning and leadership forums, contributing to annual planning, QBRs, and roadmap reviews. Communicate trade-offs, capacity constraints, and investment needs clearly to senior leadership. - Drive operational excellence, owning on-call processes, incident response, COE follow-ups, and continuous improvement of the team's operational posture.

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