Who are we?քp> 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 SummaryOur 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 we plan to commercialize 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 senior productapin leader will interface with senior business leaders, engineering, and data science teams. You’ll partner directly with engineering and data science leadership as a peer, evaluating technical approaches, challenging estimates, and making build‑vs‑buy decisions. You won’t just gather requirements and hand them off; you’ll shape solutions.Key priorities include building our Product 360 capability—a unified view of customer, product, and transaction data that will power pricing optimization, solution design, and network‑intelligence products to help customers optimize their multi‑cloud interconnection footprint.ResponsibilitiesBuild the product strategy and roadmap; own key productsDevelop the Data andégal‑AI product strategy for GMPO, aligned to business goals and prioritized against real constraintsLead development of a unified Product 360 view that integrates customer firmographics, behavioral data, product usage, and transaction historyDevelop graph‑based views of customer network topology to identify optimization opportunities, redundancy gaps, and capacity planning needsPartner with engineering as a technical peerWork side‑by‑side with engineering and data science leadership to evaluate technical options, identify technical trade‑offs, estimate effort,



and make architecture recommendations where applicableReview and assess data models, pipeline designs, and system architectures; identify risks and trade‑offs before they become problemsCritique and challenge inflated estimates and oversimplified proposals; know when a simple request is actually complexGuide engineering toward pragmatic solutions when requirements are ambiguous or shiftingDrive business impact through stakeholder partnershipBuild trust‑based relationships with senior business stakeholders by understanding their strategy, pain points, and how data and AI solutions can helpRun Bildern quarterly portfolio reviews to ensure delivery stays on track and aligned to business needsSet clear expectations, push back on low‑value requests, and educate stakeholders on what’s possible and what’s notFrame ambiguous problems, generate hypotheses, and drive to recommendations when there’s no transparent precedentManage through transition and complexityLead data product continuity during a major technology stack migration; ensure critical reporting capabilities remain intact as systems transition over multiple quartersPartner with engineering to design interim solutions that bridge Allianz and new data models during migrationBalance strategic roadmap work with operational needs; protect time for building while keeping the lights on for products in ‘maintenance’ modeBring outside‑in perspectiveStay current on analytics, AI/ML, and data product trends; bring relevant innovations (Productischt 360 approaches, AI‑augmentedi BI, knowledge graphs) to inform roadmap decisionsServe as a trusted technical advisor to business partners on what’s emerging and what’s hypeQualificationsRequired10+ years of professional experience, including 6+ years in product management for enterprise data platforms, reporting and analytics products, or AI/ML productsPrior hands મૂળ technical experience as a data engineer, software engineer, or data scientistDeep fluency in SQL and data modeling – you can inspect a schema, identify problems, evaluate query performance, and discuss normalization trade‑offsTrack record of partnering with engineering leadership as a technical peer, not just a requirements‑passerProven ability to drive prioritization, make trade‑offs,



and push back on stakeholders when neededStrong communication skills; able to simplify complex technical concepts for business audiencesExperience operating in a highly cross‑functional, global businessPreferred / Nice to haveExperience managing AI/ML product development end‑to‑end, from problem framing through deployment and iterationExperience building customer‑facing data products, not just internal tools / dashboardsExperience building Customer 360 or product 360 data products, including entity resolution and identity matching across multiple source systemsExperience with building LLM‑ready semantic layer – ensure semantic layer is governed, well‑modeled, and reliableCloud data platform expertise (e.G., BigQuery, Snowflake, Databricks כח, Redshift)Familiarity with MLOps concepts: feature stores, model serving, monitoring, retrainingเข้าสิยาIndustry background in cloud infrastructure, B2B SaaS, data centers, telecommunications, or multi‑cloud networkingSkillsAble to break down ambiguous, cross‑functional problems and drive to a solution when there’s no clear precedentComfortable reading and critiquing technical artifacts – data models, architecture diagrams, pipeline designs – and asking the right questions when something doesn’t add upAble to quickly t‑shirt‑size level of effort for data and AI initiatives across product and engineeringEfficiently translate between engineering and business – simplifying technical trade‑offs for executives while maintaining credibility with engineersDrives decisions forward; knows when to build consensus and when to make the call and move onTakes ownership of outcomes, not just delivery; holds themselves and partners accountable to business impactCanada – Toronto Office TRO : 182,000 – 272,000 CAD / AnnualUnited States – Dallas Infomart Office DAI : 177 quien 265,000 USD / AnnualEquinix is an Equal Employment Opportunity and, in the U.S., an affirmative action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy/childbirth or related medical conditions, sexuality orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political/organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.We use artificial intelligence in our hiring process. Learn more here.#J-18808-Ljbffr

📌 Director, Data Product Management - C$177,000 - C$272,000 A Year (Toronto)
🏢 Equinix
📍 Toronto