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Director, Data Product Management

Job in Toronto, Ontario, M5A, Canada
Listing for: Equinix
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Data Engineer, AI Engineer
Job Description & How to Apply Below

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.

A career at Equinix means being at the center of shaping what comes next and amplifying customer value through innovation and impact. You’ll work across teams, influence key decisions, and help shape the path forward. You’ll find belonging, purpose, and a team that welcomes you—because when you feel valued, you’re empowered to do your best work.

Job Summary

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.

Responsibilities

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 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

  • 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; ensure critical reporting capabilities remain intact as systems transition over multiple quarters

  • Part…

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