Sr. Group Product Manager - Data Enablement

Vertiv Group • Westerville, OH

17h

About The Position

Job Summary Vertiv is building a modern, intelligent data ecosystem that powers world‑class operations, customer experiences, and AI‑driven decision-making. As we accelerate our digital and AI transformation, high‑quality, governed, and accessible data is at the center of how we operate. We are seeking a Sr. Group Product Manager – Data Enablement to lead the Data Products strategy, and execution for Vertiv’s enterprise data and core data platform capabilities. This includes applying Agile Scrum mindset to manage Enterprise Data as an Asset – with value-focused portfolio of domain-aligned and source-aligned Data Products powered by a semantic layer, data quality, metadata, and multiple consumption modes (APIs, BI dashboards, AI Agents). This role will partner closely across business domains (OTO/OTC, Manufacturing, Supply Chain / Procurement, Order Fulfillment, Finance and others) to ensure that data is well‑managed, trusted, discoverable and usable across the company. This role is ideal for a product leader who thrives at the intersection of business strategy, data architecture, and modern product thinking—and who can lead cross‑functional teams in a scaled, enterprise environment. About the Team The Enterprise Data team is responsible for building Vertiv’s foundational data ecosystem that enables the company to scale AI, analytics, and operational intelligence. Our mission is to ensure that: Data is well‑managed and structured through automated controls and consistent data practices. Data is easily available, discoverable and usable through well-designed data products, discoverability, metadata, and semantic consistency.

Requirements

• 10+ years of product management experience (data, platforms, or enterprise SaaS preferred).
• Demonstrated success leading complex cross-functional initiatives at scale.
• Good understanding of modern data architectures: data lakes, data products, semantic layers, APIs, MDM, metadata management.
• Ability to convert ambiguous business needs into structured product roadmaps and measurable outcomes.
• Experience working with engineering teams on cloud data platforms
• Excellent communication, leadership, and stakeholder engagement skills

Nice To Haves

• Experience with AI platforms and enabling data for AI agents.
• Experience establishing or scaling domain data product operating models in Manufacturing domain areas.

Responsibilities

• Data Products & Domain Enablement Own the Roadmap for defining and scaling the enterprise model for domain-owned data products (starting with O2C and Finance). Drive value and consumption of Data Products. Ensure all data products meet standards for quality, lineage, SLOs, contracts, security, and interoperability.
• Data Management Drive automated governance across the data lifecycle in Enterprise Data Lake - from ingestion to publishing to consumption in Business-ready and AI-ready consumption layers. Partner with Engineering, Architecture, and Security to operationalize Data Management policies and controls. Own the roadmap for Data Quality measurement in the data lake (DQ scores, rules, issues workflow, observability).
• Data Foundation & Common Ecosystem Lead the product roadmap and its disciplined execution for core data capabilities: Enterprise data lake (powered by Snowflake) Data marketplace Data Management capabilities including Metadata, lineage, and observability Partner with engineering to evolve the platform for scale, performance, and self-service enablement. Execute work in bi-weekly Sprints with user demos and feedback to drive adoption and value of Enterprise Data capabilities (Agile Scrum)
• Strategic Data Leadership Develop and execute the multi-year product strategy for enterprise data foundations and domain data products. Influence senior business and technology stakeholders, aligning them behind a consistent data product operating model. Translate complex business needs into scalable data capabilities.
• Product Execution Lead execution working closely with Engineering teams across discovery, prioritization, roadmap creation, and release planning. Create clear problem statements, outcome-driven metrics, and success criteria. Partner with Engineering, Data Architecture, Governance, MDM, Security, Analytics, and AI Engineering. Work closely with domain leaders (Sales Ops/O2C, Finance, Supply Chain) to ensure adoption and enterprise impact.
• Quality, Risk & Compliance Ensure data products adhere to data quality, lineage, privacy, and SLO/SLA expectations. Mitigate risks proactively with internal controls, transparency, and measurement.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed