Analytics Engineer 5 - Ads Revenue Analytics

Netflix is a leading entertainment company focused on pushing the boundaries of storytelling and technology. They are seeking a Senior Analytics Engineer to lead the development of a unified revenue analytics narrative and strategy for their global Ads business, focusing on operationalizing core revenue datasets and driving business insights.

Responsibilities:

• Lead the analytics vision for unified revenue measurement across Netflix Ads, designing and implementing frameworks to harmonize, quantify, and report on diverse revenue streams, including new content formats Netflix is launching, like Live and Free-to-air Broadcasting
• Act as the lead Semantic Architect for revenue, driving consensus across F&S, Accounting, and Product, and codifying those agreed-upon definitions into the Ads Metrics Catalog (AMC) and our underlying semantic models
• Build scalable, transparent data models and dashboards—in partnership with Data Engineering—that provide real-time and periodic insights into revenue streams, metric definitions, and the impact of adjustments, supporting daily operational needs and strict financial and SOX compliance reporting
• Drive the narrative around how core revenue definitions impact downstream performance metrics (like CPM and CPS), conducting deep-dive research to explain the why behind metric movements
• Act as a subject matter expert in revenue analytics, piloting scalable solutions for complex treatments (e.g., invoice discounts, agency fees, FX rates, makegoods, and integrated marketing fees), and driving innovation and transparency in how Netflix measures and communicates advertising revenue
• Serve as the integration layer for revenue data. While partner teams may own localized source data (Sales, Live, etc.), you will be responsible for aggregating, harmonizing, and exposing the overarching executive revenue views in core reporting surfaces

Requirements:

• Experience working with financial datasets, revenue accounting, or ad-tech monetization analytics
• A “Data Product Owner” mindset. You are comfortable with ambiguity and recognize that defining the metric across a matrixed organization is just as important as writing the code to build it
• Communication superpower — the ability to communicate, influence, and connect the dots between insights and actions across a variety of stakeholders
• Fluency in SQL, workflow orchestration tools like Apache Airflow, and at least one analytics and scripting language like Python
• Mentors, brainstorms with, and enables others, especially within your functional area
• A proven track record of balancing the need to move quickly with the high rigor and accuracy required for executive and financial reporting
• Strong analytical rigor combined with the ability to conduct independent research and explain complex metric variances to senior leadership
• Experience building or working with semantic modeling tools like LookML for creating and managing metric contracts
• Curiosity or practical experience building with emerging AI technologies (e.g., Agentic AI)