Amazon.com Services LLC
Technology
DataEngineeringManager,PlanningandAudienceInsights
Neural analysis suggests this role is
optimal for Manager candidates.
“Data Engineering Manager, Planning and Audience Insights at Amazon.com Services LLC. Skills: Data Engineering, AI/ML, Data Platform, Team Leadership. Lead and develop senior data engineers. Hire senior data engineers”
Industry & Context.
Root cause analysis; Troubleshooting
On-call processes
What They're Looking For.
Must Have
7+ years data engineering experience, Experience managing data/BI team, 5+ years processing data with massively parallel technology, 3+ years developing/operating large-scale data structures for BI analytics, Experience leading/influencing data/BI strategy, Experience communicating to senior management, Experience communicating to customers, Experience in scripting or programming language
Nice to Have
Experience with big data technologies, Experience with AWS Tools, Experience working with Data & AI technologies, Knowledge of digital creative production, Knowledge of ad serving, Knowledge of cross-channel attribution, Knowledge of media analytics, Experience developing cloud native CI/CD workflows
What You'll Do.
Lead and develop senior data engineers
Hire senior data engineers
Mentor senior data engineers
Set technical direction
Manage performance of engineers
Manage growth opportunities for engineers
Own data platform strategy
Own data platform roadmap
Manage Redshift infrastructure
Optimize Redshift infrastructure
Ensure Redshift performance
Ensure Redshift cost efficiency
Ensure Redshift availability
Ensure Redshift scalability
Own data pipelines for AI tools
Ensure reliable data flows
Ensure high-quality data flows
Drive data engineering for applications
Establish data governance standards
Enforce data governance standards
Establish data quality standards
Enforce data quality standards
Establish data reliability standards
Enforce data reliability standards
Implement data quality frameworks
Partner cross-functionally
Translate business requirements
Design scalable data architecture
Design pipeline solutions
Represent data engineering in forums
Contribute to annual planning
Contribute to roadmap reviews
Communicate trade-offs
Communicate capacity constraints
Communicate investment needs
Drive operational excellence
Own on-call processes
Manage incident response
Manage COE follow-ups
Improve operational posture
How You'll Work.
Team & Collaboration
Product managers; Data scientists; Analytics; BI engineers; Software engineers; Content programmers; Marketing strategists; Senior leadership
Communication Scope
Verbal communication; Written communication
Process & Methodology
Roadmap planning, Annual planning, QBRs
Full Job Description
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.
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