Staff Product Designer, Data Platform - Analytics & Data Experience

Netflix is a leading entertainment company that is pushing the boundaries of storytelling and technology. They are seeking a Staff Product Designer to shape the future of analytics and data experiences, focusing on designing intuitive workflows for data practitioners to enhance productivity and trust in insights.

Responsibilities:

• Lead design strategy for analytics and data experiences that span multiple teams, creating intuitive workflows that enhance practitioner productivity
• Define, evolve, and drive adoption of design patterns and components that scale across the platform
• Identify opportunities for innovation through user research and technical insight
• Create cohesive, end-to-end experiences that reduce cognitive load
• Partner with product and engineering to define and improve how we measure practitioner experiences
• Anticipate emerging needs and help frame design problems early
• Drive end-to-end design for interdependent data workflows (development, modeling, orchestration, analysis, troubleshooting), and influence cross-functional roadmaps
• Craft and validate prototypes that effectively communicate solutions
• Establish scalable design practices and foundational patterns
• Scope and negotiate realistic deliverables with partners
• Mentor designers and partner teams; help grow shared understanding and adoption of effective design practices
• Partner with, influence, and co-create long-term strategy with product and engineering leadership to drive critical data platform initiatives
• Facilitate design workshops and creative sessions with technical stakeholders and build consensus on complex strategic direction
• Articulate compelling design visions and build durable alignment with senior leadership, connecting technical challenges to business outcomes
• Build strong relationships across platform teams
• Lead through influence across teams to create coherent, system-wide experiences and align on shared goals

Requirements:

• 8+ years as a Product Designer (or equivalent experience)
• Experience designing analytics/data platform tools, developer/data tools, or analogous complex technical products
• Strong portfolio showing system‑level product work and the impact of your design leadership, including initiatives that span multiple teams
• Proven track record of leading design initiatives from concept to launch
• Proficient in design tools (Figma, etc.) and prototyping technologies
• Strong systems thinking and ability to design scalable solutions for complex data/analytics challenges
• Successfully led design strategy for complex technical products
• Proven track record of influencing and aligning cross-functional partners without direct authority
• Ability to navigate ambiguity, create clarity, and move complex initiatives forward with partners
• Excellence in communicating design decisions to technical audiences
• Demonstrated success in mentoring designers and improving team practices
• Strong ability to work autonomously and drive initiatives independently
• Skill in sequencing and communicating long-term vision through incremental steps
• Ability to collaborate effectively with engineers (coding skills not required)
• Literacy in analytics and data engineering workflows (e.g., Git‑based / dbt-style project patterns with tests, documentation, CI, and pre‑commit validation) and empathy for code‑first users in IDE/CLI
• Fluency in semantic and metrics modeling and headless BI/semantic layer patterns; understanding of metric definition, reuse, and governance
• Ability to integrate governed metrics into BI/reporting tools and design report‑builder UX with strong defaults and appropriate constraints
• Strength in designing data‑dense, system‑oriented interfaces (e.g., lineage graphs, dependencies, metric lifecycle) with embedded trust signals (freshness, test status, ownership, change history)
• Understanding of permissions/entitlements, data contracts, and compliance constraints and their UX implications
• Experience identifying emerging shifts (e.g., semantic layer/metrics ecosystems, AI‑assist in analytics) and evolving UX accordingly
• Applied AI/ML‑enhanced experiences a plus (e.g., conversational queries, guided analysis)