Product Manager - Senior Staff - Data & AI

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 Description About the Role We're looking for a Senior/Staff Product Manager to join our Data & Analytics team and own the product strategy for data platforms, analytics tooling, and AI-driven capabilities. This role sits at the intersection of data engineering, business strategy, and applied AI — you'll translate complex business needs into a clear product roadmap, while working hand-in-hand with data engineers to ship scalable, reliable, and high-impact solutions. This is a high-visibility, cross-functional role for someone who can operate at both strategic and technical depth, partner effectively with engineering and business stakeholders, and has hands-on experience shipping AI/ML-powered products. What You'll Do Product Management for Data, BI and AI product Manage and execute the data analytics product vision to help business teams adopt data and use it confidently for decision-making. Lead end-to-end delivery of AI-powered analytics products — from problem framing and data feasibility assessment through model evaluation, deployment, and adoption. Define success metrics, build business cases, and prioritize a roadmap balancing technical debt, platform scalability, and business impact. Provide statistical techniques, quantitative data analysis, predictive analytics, and scenario-based analysis to support product decisions. Cross-Functional Partnership Engage with cross-functional business and IT teams to understand requirements, analyze, design, and help build solutions for analytics and data science products. Partner closely with Data Engineering to design scalable data pipelines, infrastructure, and platform capabilities that support analytics and AI use cases. Work directly with business partners (Sales, Marketing, Customer Success...) to identify high-value problems, gather requirements, and translate them into actionable product specs. Collaborate closely with analysts and data scientists across the organization, including on model development, evaluation, and responsible AI practices (bias, explainability, governance). Analyze complex requirements and translate them into simple, actionable user stories. Maintain deep knowledge of cross-functional data and ensure data quality on all products launched. Delivery & Execution Build dashboard prototypes to help business stakeholders visualize end products. Get involved in testing analytic products for functionality, user interface, and data quality. Provide technical support to business teams for self-serve analytics; define best practices and develop user guides. Follow agile methodologies and deliver continuous enhancements to products. Optimize release management to strike the right balance between business goals and delivery capacity. Identify and manage risks in release delivery and communicate clearly with stakeholders, including mitigation plans. Debug and identify root causes for critical issues and provide solution recommendations. Ensure data security and compliance measures are in place for every product delivered. Leadership & Documentation Support senior management by creating architecture, project management, and roadmap documentation. Own the product lifecycle: discovery, prioritization, requirements, launch, and post-launch iteration. Evangelize data-driven and AI-driven decision-making across the organization. Mentor junior PMs and contribute to product process and best practices (especially at the Staff level). Maintain a strong personal base of knowledge on data platform technology, industry practices, trends, and emerging issues. What You'll Need Education Master's Degree in Statistics, Analytics, Mathematics, Economics, or a related quantitative field (preferred). Experience 8+ years of product management experience (3+ years as a Data Analyst/similar role supporting cross-functional global business units, for candidates coming from an analytics background), with at least 2–3 years focused on data platforms, analytics, or AI/ML products. Demonstrated experience shipping AI/ML-powered features or products (e.g., recommendation systems, predictive models, LLM-based applications, automation tools) — this is required. Proven track record partnering closely with data engineering teams on data infrastructure, pipelines, or platform-level products. Experience working directly with business stakeholders to translate ambiguous needs into structured product requirements. Experience building customer-centric data products, sales-centric analytic products, and executive metrics/reporting. Experience with data from the Customer Experience and Sales domains. Experience in the data center domain and knowledge of data center products are nice-to-have. Skills Strong technical fluency: comfortable discussing data architecture, ETL/ELT pipelines, data modeling, and ML/AI concepts with engineering teams. Strong statistical and data analysis skills, including regressions, classification, anomaly detection, and hypothesis testing, with experience applying these techniques in real analyses. Excellent communication and stakeholder management skills; able to flex between technical depth and business-level storytelling. Strong analytical skills in breaking down complex problems, processes, and systems to propose solutions. Ability to document and prototype business use cases and data flows. Strong quantitative skills; comfortable with SQL and interpreting data to drive decisions. Experience with agile product development practices, roadmap planning, and prioritization frameworks. Familiarity with the AI/ML lifecycle (data prep, model training/evaluation, deployment, monitoring) and responsible AI considerations. Proven experience building dashboards in Tableau, Power BI, QlikView, or similar tools. Ability to understand complex data models and connect to varied data sources such as SFDC, Exasol, Google BigQuery, and AWS. Tableau certification is desirable, along with experience on Tableau Online (cloud), Tableau Server, and Tableau Prep. Nice to Have Prior experience as a data analyst, data engineer, or data scientist before transitioning into product. Experience with generative AI / LLM-based product development. Note - T his is a business facing role we need this positionsupporting position to be remote and provide support during US hours (4:00 PM IST to 12:00 AM IST) Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form . Equinix 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, sexual 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 .