Job Description
Role Summary
The Senior Manager, S2P Analytics & Master Data serves as the business owner for the Source-to-Pay (S2P) data and analytics foundation. This role ensures that supplier, taxonomy/category, preferred supplier, item/service, contract, risk, and related reference data are accurate, governed, scalable, and fit for purpose—while translating that data into trusted insights, executive narratives, self-service analytics, automation, and AI-enabled decision support.
The role leads the business-side governance model, master-data lifecycle, data quality standards, analytics product portfolio, insight-generation capability, and enabling platform requirements across the S2P lifecycle. It partners closely with S2C and P2P Process & Platform Enablement, Strategy/Governance/Excellence, SBE, Finance, Legal, Risk, IT/Digital, enterprise Data Governance, and S2P Transformation teams.
This leader makes data a trusted business asset that powers reliable operations, decision-grade reporting, controls, intelligent routing, automation, performance management, and future-state AI capabilities.
Key Responsibilities
1. S2P Master Data, Taxonomy & Governance Ownership
- Serve as the senior business lead for S2P data domains, including supplier master, third-party entity types, taxonomy/category structures, preferred supplier designation, item/service data, contract/reference data, risk attributes, and related reference data.
- Own business-led governance standards for data ownership, stewardship, approval workflows, change control, escalation paths, and decision rights across Procurement, Finance, Legal, Risk, IT/Digital, and enterprise data teams.
- Establish data definitions, semantic standards, lineage expectations, quality requirements, and governance routines that enable consistent reporting, automation, analytics, and AI use cases.
- Ensure taxonomy and master-data standards support buying-channel guidance, preferred supplier utilization, supplier segmentation, risk screening, compliance monitoring, routing, value tracking, and performance analysis.
2. Master Data Lifecycle, Process & Platform Enablement
- Lead business requirements and lifecycle processes for data creation, validation, enrichment, maintenance, synchronization, change control, retirement, exception management, and remediation.
- Embed data management requirements into S2C, P2P, TPRM, CLM, intake/orchestration, and buying-channel workflows rather than treating data management as a separate manual activity.
- Partner with IT/Digital and platform owners to define requirements for MDM, Coupa, Icertis, ProcessUnity, Zip, VDP/Snowflake, Power BI, and related integrations.
- Drive standardization, integration, and automation to reduce rework, duplicate maintenance, manual spreadsheets, data defects, and point-to-point workarounds.
3. Analytics Product Ownership & Decision Support
- Own the S2P analytics product portfolio, including executive dashboards, KPI views, category and program dashboards, standard performance scorecards, self-service analytics, and automated insight products.
- Define and maintain an integrated data and analytics roadmap based on business priorities, stakeholder needs, technology maturity, data risk, automation dependency, and transformation value.
- Ensure each analytics product has a defined audience, business purpose, trusted KPI set, data source, adoption plan, and operating cadence.
- Translate data into clear executive narratives that explain what changed, why it matters, and what decisions or actions are required.
- Generate decision-ready insights across spend, sourcing, suppliers, P2P performance, value delivery, savings visibility, compliance, cycle times, preferred supplier utilization, supplier risk, and SBE visibility.
4. Data Quality, Controls, Compliance & Risk Enablement
- Define data-quality rules, validation logic, exception thresholds, monitoring routines, and remediation playbooks across S2P master-data and analytics domains.
- Partner with Compliance, Risk, Finance, Internal Audit, TPRM, Sourcing, and Procurement Operations to ensure data supports regulatory expectations, audit readiness, financial controls, segregation of duties, risk visibility, and policy adherence.
- Reduce operational, compliance, and reporting risk resulting from incomplete, inconsistent, duplicative, or poorly governed data.
5. Analytics Automation & AI Enablement
- Lead the business roadmap for data and analytics automation, including data validation, enrichment, deduplication, exception detection, stewardship workflows, automated insights, conversational analytics, and agent-enabled reporting.
- Partner with IT/Digital, enterprise Data Governance, and data-platform teams to establish AI-ready data foundations, including governed definitions, semantic consistency, lineage, quality controls, access standards, and Snowflake/VDP readiness.
- Evaluate and enable capabilities such as AI agents, natural-language analytics, automated insight generation, exception-based reporting, and self-service decision support.
- Identify opportunities to reduce manual reporting and data-cleanup effort, shifting capacity toward performance dialogue, insight generation, governance, and scalable capability building.
6. Intake, Operating Model & Adoption
- Design and lead a sustainable operating model for S2P data stewardship, analytics intake, prioritization, backlog management, issue resolution, and delivery governance.
- Establish predictable routines for data-quality monitoring, taxonomy changes, dashboard refreshes, performance reviews, stakeholder feedback, and roadmap decisions.
- Define clear accountability across Procurement Operations, Sourcing, Finance, Legal, Risk, IT/Digital, enterprise Data Governance, and offshore or managed-service support teams.
- Drive adoption through standards, documentation, playbooks, training, office hours, stakeholder engagement, and clear role definitions.
- Differentiate and spearhead the strategic ownership of data governance, analytics products, insight delivery, and enablement from the day-to-day report production, dashboard maintenance, transactional execution, and operational data cleanup in parallel.
7. Cross-COE & Cross-Platform Collaboration
- Partner with P2P Process & Platform Enablement to ensure supplier, item/service, and reference data support clean transaction execution, control integrity, and operational performance visibility.
- Partner with S2C Process & Platform Enablement to ensure sourcing and contracting activities create high-quality downstream data and enable sourcing-performance analytics.
- Partner with Strategy, Governance & Excellence, SBE, TPRM, and Supplier Performance leaders to support trusted metrics and visibility into savings, value delivery, SBE performance, risk, supplier segmentation, and program outcomes.
- Coordinate with IT/Digital, enterprise Data Governance, MDM, VDP/Snowflake, and platform teams on architecture, integrations, access, data flows, tooling alignment, and long-term scalability.
Ownership Boundaries
This role owns:
- Business governance, standards, roadmap, requirements, and operating model for S2P master data, taxonomy, reference data, analytics products, insight delivery, and AI-enabled analytics.
- Data-quality frameworks, stewardship routines, analytics intake, analytics-product adoption, and business requirements for data and analytics platforms.
- Strategic level oversight of Day-to-day operational report production or routine dashboard maintenance
This role does not Own:
- Transaction execution, sourcing execution, or supplier relationship strategy.
- Savings methodology, target setting, or SBE program ownership.
- Policy definition, legal determinations, or enterprise technology delivery.
- The role partners with accountable process, program, finance, governance, supplier, and platform owners to ensure their capabilities use consistent, trusted, and actionable data.
Qualifications & Experience
Required:
- 8+ years of experience in master data management, data governance, procurement analytics, spend analytics, sourcing/procurement insights, business intelligence, procurement operations, finance, supply chain, or Source-to-Pay environments.
- Strong understanding of how supplier, taxonomy, contract, risk, preferred supplier, and reference data affect S2P execution, controls, analytics, automation, reporting, and decision-making.
- Demonstrated experience defining business-side data-governance models, including ownership, stewardship, quality standards, approval workflows, change control, and escalation routines.
- Experience building executive dashboards, KPI frameworks, operational scorecards, analytics roadmaps, and decision-support narratives.
- Ability to translate business needs into practical data, process, platform, integration, reporting, automation, and AI-readiness requirements in partnership with IT/Digital and enterprise data teams.
Preferred:
- Experience enabling supplier MDM, taxonomy/category structures, preferred supplier data, supplier segmentation, third-party entity types, CLM, TPRM, or related data dependencies at scale.
- Experience improving data quality through process redesign, platform enablement, integration, automation, and operating-model change.
- Experience enabling self-service analytics, automated insights, AI-assisted reporting, conversational analytics, or agent-enabled capabilities.
- Familiarity with Coupa, Icertis, ProcessUnity, Zip, MDM or MDG platforms, Data Lakes (Snowflake), Power BI, or comparable procurement and data ecosystems.
- Experience in a global COE, shared-service, transformation, enterprise-governance, or digitally enabled procurement environment.
Leadership Attributes
Business-oriented data and analytics leader who views data as a strategic enabler of execution, insight, controls, automation, user experience, and AI readiness.
Insight-driven decision partner who focuses on actions, performance outcomes, and credible executive storytelling—not simply data availability.
Systems thinker who connects data design to process flows, platform behavior, reporting outputs, risk controls, and user adoption.
Strong cross-functional influencer who can advance standards, stewardship, accountability, and adoption through partnership rather than direct authority.
Future-oriented capability builder who can move the organization from manual reporting and fragmented data management to scalable data products, automation, self-service analytics, and AI-enabled decision support.
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Pay Range:
$135,400 - $203,100
At Vertex, our Total Rewards offerings also include inclusive market-leading benefits to meet our employees wherever they are in their career, financial, family and wellbeing journey while providing flexibility and resources to support their growth and aspirations. From medical, dental and vision benefits to generous paid time off (including a week-long company shutdown in the Summer and the Winter), educational assistance programs including student loan repayment, a generous commuting subsidy, matching charitable donations, 401(k) and so much more.
Flex Designation:
Hybrid-Eligible Or On-Site Eligible
Flex Eligibility Status:
In this Hybrid-Eligible role, you can choose to be designated as:
1. Hybrid: work remotely up to two days per week; or select
2. On-Site: work five days per week on-site with ad hoc flexibility.
Note: The Flex status for this position is subject to Vertex’s Policy on Flex @ Vertex Program and may be changed at any time.
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