Data Product Manager

At Globality, we build agentic technology that transforms how global enterprises source goods and services — autonomously, at scale, and without the inefficiencies that have defined procurement for decades. Our platform interprets purchase intent, generates sourcing materials, evaluates suppliers, and executes negotiation strategies without manual intervention.

Every sourcing event run on Glo generates structured data on purchase intent, supplier pricing and performance, negotiation outcomes, and award decisions. As a Data Product Manager at Globality, you will own the strategy for capturing, structuring, and compounding that data into a proprietary asset that makes Glo smarter with every event and makes Globality's market position defensible. You will set the requirements forwhat data we collect, how it is structured and governed, and how it flows back into the platform to improve agent performance and customer outcomes. You will also own the analytics and benchmark products that give customers insight into their sourcing results. You will partner with Engineering, Machine Learning, the AI Product Manager, and Product leadership to run data as a product with its own roadmap, users, and measurable return. 

• →Own the data product strategy and roadmap, defining how Globality captures, structures, and compounds customer and sourcing data into a defensible, proprietary asset. 
• →Identify which data creates durable competitive advantage, including purchase intent, should-cost benchmarks, supplier pricing and performance, negotiation outcomes, and award decisions, and prioritize investment accordingly.
• →Design the instrumentation strategy that captures high-value signals at every step of the intake-to-award process,in partnership with the product managers who own each workflow, closing gaps where data is lost or left unstructured.
• →Define canonical data models, taxonomies, and entity resolution for suppliers, categories, and commercial terms so data from every customer, ERP platform, and procurement system can be unified and reused across the platform.
• →Build the feedback loops that turn sourcing outcomes into training data, evaluation sets, and benchmarks that improve Glo's agents, including target pricing, supplier discovery, negotiation strategy, and award recommendations.
• →Partner with the AI Product Manager, Machine Learning and Engineering to make data readily usable by models and agents, including labeled datasets, feature pipelines, and retrieval sources.
• →Define data-powered product capabilities, such as market pricing and should-cost benchmarks, that deliver customer value only Globality's aggregated data can provide, working with Product leadership to decide which are worth building.
• →Work with Legal, Security, and Sales to establish the data rights, consent, and contractual frameworks that allow Globality to use aggregated and anonymized data across customers.
• →Set standards for data quality, coverage, and freshness, and measure the value of the data asset through metrics such as category coverage, model performance lift, and improvement in customer outcomes.
• →Own the roadmap for customer-facing analytics, such as spend and savings reporting and customer insight dashboards, in partnership with Product leadership.
• →Define the metrics that show customer results, including cycle time, savings, spend under management, supplier participation, and award outcomes, keep their definitions consistent across products, and document them in a shared data dictionary.
• →Ensure customer data is handled in line with SOC 2 Type 2, ISO 27001:2022, GDPR, and CCPA requirements, including data segregation and access controls. 

• 5+ years of product management experience, including 3+ years owning data platform, data infrastructure, or AI/ML data products
• A track record of turning proprietary data into a strategic asset, such as data network effects, industry benchmarks, or training data that measurably improved model performance
• Deep understanding of data architecture, including data modeling, pipelines, warehouses and lakehouses, entity resolution, and master data management
• Experience working closely with ML teams on training data, labeling, evaluation datasets, and feedback loops for machine learning or LLM-based systems
• Experience structuring and normalizing messy, multi-source enterprise data, ideally from ERP, procurement, or financial systems
• Working knowledge of data rights, privacy, and governance in multi-tenant B2B SaaS, including anonymization and aggregation of customer data
• Strong technical fluency, including SQL, with the ability to assess data quality and validate assumptions independently
• A strategic, business-oriented mindset, with the ability to articulate the economic value of data and make the case for investment to executive leadership
• Experience turning customer or operational data into analytics, dashboards, or benchmarks used by external customers
• Experience with procurement, sourcing, or spend data is a strong plus

The opportunity is enormous. Enterprise procurement is one of the last major business functions to be transformed by AI. We're not optimizing at the margins — we're fundamentally rethinking how trillions of dollars get spent.

The team is world-class. Our leadership team brings decades of experience from leading global enterprises, and our culture is built for people who want real ownership, not titles.

You'll have real impact. This isn't a role where you execute someone else's playbook. You'll shape the strategy, build the programs, and see the direct business impact of your work.

We work together — literally. We’re in the Palo Alto office 4 days a week because the best ideas—and the fastest decisions—happen face to face.