Director, Data Product Management

Who are we?

Equinix is the world’s digital infrastructure company® shortening the path to connectivity to enable the innovations that enrich our work, life and planet. A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.

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 and automated data center cage design. As we scale, we transform internal operational and analytical data into unified, governed, high-quality assets for Equinix, and plan to commercialize differentiated data and insights offerings for external customers.

• Build the product strategy and roadmap; own key products
  • 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.
• Partner with engineering as a technical peer
  • Work side-by-side with engineering and data science leadership to evaluate technical options, identify tradeoffs, estimate effort, and make architecture recommendations.
  • 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.
• Drive business impact through stakeholder partnership
  • 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.
• Manage through transition and complexity
  • Lead data product continuity during a major technology stack migration; keep critical reporting capabilities 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.
• Bring outside-in perspective
  • 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.

• 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 – able to interpret schemas, 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.

• Experience managing AI/ML product development end-to-end,…