Director of Data Product Management, Equinix

• 10+ years of professional experience, including 6+ years in product management for enterprise data platforms, reporting and analytics products, or AI/ML products
• Prior hands-on technical experience as a data engineer, software engineer, or data scientist
• Deep fluency in SQL and data modeling - you can look at a schema and identify problems, evaluate query performance, and discuss normalization tradeoffs
• Track record of partnering with engineering leadership as a technical peer, not just a requirements-passer
• Proven ability to drive prioritization, make tradeoffs, and push back on stakeholders when needed
• Strong communication skills; able to simplify complex technical concepts for business audiences
• Experience operating in a highly cross functional, global business
• Able to break down ambiguous, cross-functional problems and drive to a solution when there's no clear precedent or playbook
• Comfortable reading and critiquing technical artifacts - data models, architecture diagrams, pipeline designs - and asking the right questions when something doesn't add up
• Able to quickly T-shirt size level of effort for data and AI initiatives across product and engineering
• Able to effectively translate between engineering and business - simplifying technical tradeoffs for executives while maintaining credibility with engineers
• Drives decisions forward; knows when to build consensus and when to make the call and move on
• Takes ownership of outcomes, not just delivery; holds themselves and partners accountable to business impact

Desirable

• Our data products power the insights, decisions, and operations of teams across Equinix
• We build and manage core data platform capabilities, reusable data models, semantic layers, decision-ready dashboards, conversational BI, and custom AI solutions including interconnection recommendation engines, automated data center cage design, etc
• As we scale, we are transforming internal operational and analytical data into unified, governed, high quality assets for Equinix, and we plan to build toward commercializing differentiated data and insights offerings for external customers
• We're looking for a Director of Data Product Management to develop the data and AI product roadmap for our Global Markets and Product Organization (GMPO)
• This is a senior product leader role, that will interface with both senior business leaders and engineering, data science team
• You'll partner directly with engineering and data science leadership as a peer - someone who can evaluate technical approaches, challenge estimates, and make sound build-vs-buy decisions
• You won't just gather requirements and hand them off; you'll shape solutions
• Key priorities for this role include building our Product 360 capability, a unified view of customer, product, and transaction data that will power pricing optimization, solution design, and developing network intelligence products that help customers optimize their multi-cloud interconnection footprint
• This role resides within Equinix’s Enterprise Data & Analytics team, and reports to the Senior Director of Data Product, GMPO and Business Operations
• Develop the Data and AI product strategy for GMPO, aligned to business goals and prioritized against real constraints
• Lead development of a unified Product 360 view that integrates customer firmographics, behavioral data, product usage, and transaction history
• Develop graph-based views of customer network topology to identify optimization opportunities, redundancy gaps, and capacity planning needs
• Develop business cases, drive prioritization and resource allocation to deliver highest-ROI outcomes; say no when needed and make the case for it
• Work side-by-side with engineering and data science leadership to evaluate technical options, identify technical tradeoffs, estimate effort, and make architecture recommendations where applicable
• Review and assess data models, pipeline designs, and system architectures; identify risks and tradeoffs before they become problems
• Critique and challenge inflated estimates and oversimplified proposals; know when a "simple" request is actually complex
• Guide engineering toward pragmatic solutions when requirements are ambiguous or shifting
• Build trust-based relationships with senior business stakeholders by understanding their strategy, pain points, and how data and AI solutions can help
• Run monthly/quarterly portfolio reviews to ensure delivery stays on track and aligned to business needs
• Set clear expectations, push back on low-value requests, and educate stakeholders on what's possible and what's not
• Frame ambiguous problems, generate hypotheses, and drive to recommendations when there's no clear precedent
• Lead data product continuity during a major technology stack migration; ensure critical reporting capabilities remain intact as systems transition over multiple quarters
• Partner with engineering to design interim solutions that bridge old and new data models during migration
• Balance strategic roadmap work with operational needs; protect time for building while keeping the lights on for products in ‘maintenance’ mode
• Stay current on analytics, AI/ML, and data product trends; bring relevant innovations (e.g., Product 360 approaches, AI-augmented BI, knowledge graphs) to inform roadmap decisions
• Serve as a trusted technical advisor to business partners on what's emerging and what's hype