Analytics Engineer 5 - Growth & Membership

Netflix is a company dedicated to entertaining the world through innovative storytelling and technology. They are seeking a Senior Analytics Engineer to shape the future of revenue data products within Corporate Finance, driving strategic decision-making through advanced analytics.

Responsibilities:

• Champion a “data as a product” mindset: Set the standard for robust documentation, testing, and data model design – making revenue data products easy to understand, trust, and extend
• Mentor and uplevel the team: Share best practices in analytics engineering, code quality, and documentation; coach others to adopt product-minded approaches and raise AE standards across the org
• Partner cross-functionally with Finance, Data Science, Data Engineering, and Revenue stakeholders to define the future vision for key revenue data products, surfacing opportunities for innovation and improved business impact
• Continuously improve business-critical analytics workflows for revenue that power Investor Relations reporting and all downstream revenue consumers, ensuring reliability, scalability, and transparency
• Drive root-cause analysis and ask “why” to deeply understand the drivers of revenue data issues, proactively identifying improvements to workflows, code, and models
• Implement and advocate for orchestration best practices to ensure the reliability and timeliness of revenue data pipelines
• Leverage AI tools (e.g., Claude Code, Cursor, MCP servers) to boost developer productivity and workflow efficiency, and share learnings with the team
• Contribute to the adoption of modern AE standards (e.g., WAP—Write Audit Publish) and help define best practices for documentation, testing, and code review
• Work with modern data infrastructure (Iceberg, SQL, orchestration tools), with opportunities to influence adoption of new tools (e.g., DBT, Pandas)

Requirements:

• Demonstrated ability to write clean, readable, and impactful SQL code
• Advanced SQL skills for analytics data processing (orchestration, metrics creation, documentation)
• Familiarity with DBT or other semantic data modeling tools for strong data foundations
• 8+ years in analytics/data engineering, ideally in high-stakes, business-critical data environments
• Data-as-a-product mentality and ability to influence and drive cross-functional change from specification, planning, implementation, and beyond launch
• Deep sense of ownership, curiosity, and a drive to get at the 'why' behind data and workflow design
• Proven ability to mentor, influence, and raise the bar for technical and product standards within a team
• Excellent communication skills for both technical and non-technical audiences
• Collaborative, innovative, and comfortable navigating ambiguity in a fast-moving environment
• Experience with AI tools for automation (e.g., Cursor, Claude, Commands, Rules) is a plus
• Experience with Python Pandas framework is a plus