Senior Director, Enterprise Data Management

About Versapay

Versapay is the platform that rewires AR by removing barriers to collecting and reconciling B2B payments, providing end- to-end cash flow clarity, ensuring businesses can manage working capital on their terms. By closing the loop for finance teams and their business systems, customers, and payment activity into a single intelligent ecosystem, Versapay transforms money matters into a data-driven advantage. With 10,000 customers and 5M+ companies transacting, Versapay facilitates 110M+ transactions and processes $300B+ in payments volume annually.

About the Role

We are looking for a strategic, builder-minded Senior Director of Enterprise Data Management to own and execute Versapay’s enterprise data strategy at a pivotal moment in our evolution. This leader will drive the convergence of our transactional, operational, behavioral, relational and intent data layers into a unified operational backbone — the foundational unlock for AI- powered product features, semantic data models, externalized data products, and autonomous AR workflows.

This is a high-visibility, high-impact role directly tied to our product and commercial roadmap, with a clear mandate and executive alignment behind it.

• Define and drive Versapay’s enterprise data strategy, aligning the data roadmap to product, AI, and commercial objectives.
• Lead the architectural convergence of our transactional, operational, and analytical data layers into a unified, bi-directional operational backbone.
• Own a multi-year data maturity roadmap with clear milestones across architecture, semantics, governance, and accessibility.
•  Champion a business-first data modelling philosophy: canonical hierarchies, enterprise ontologies, and shared metric catalogues that allow humans and AI agents to interpret data consistently. 

• Operationalize data governance as a first-class concern — automated classification, RBAC enforcement, platform SLAs, and certified data objects.
•  Formalize the Enterprise Data Catalogue, replacing institutional knowledge with a searchable, self-service discovery layer.
•  Deploy and maintain an executive data health dashboard to provide ongoing visibility into the health and integrity of our data estate.
• Enforce the data procurement gate, ensuring new tools and systems are reviewed and classified before entering the estate.
•  Build and own the Enterprise Data Asset Registry to enable secure, frictionless data sharing internally and with commercial partners.

• Drive data infrastructure readiness to support Versapay’s AI roadmap — from ML pipelines and LLM serving layers
  to agentic serving tiers.
• Establish formal schema contracts and semantic modelling standards that guarantee deterministic outputs for safe,
  scalable agent deployment.
•  Partner with Product and Engineering to enable agentic capabilities: reverse data flow, predictive model productization, and real-time data serving.
• Govern data and AI exposure — ensuring sensitive data stays within approved platforms and all external data products meet strict quality, lineage, and privacy standards.

• Evolve the function from ad hoc data requests to a design-first, product-oriented organization with a governed, discoverable asset registry.
• Operationalize external data products for commercialization, delivering clear value to customers within consent
  and compliance frameworks.
• Partner with the commercial team on data product strategy — turning Versapay’s proprietary network data into defensible, recurring revenue.
• Expand self-service data access for internal teams while protecting compute capacity and governance standards. 

•  Lead and grow the Data Platform Team, building a high-performing function with clear ownership across data strategy, engineering, consumption, AI compute; in tight partnership with the Embedded Analytics Team, Risk and Compliance.
•  Act as the cross-functional bridge between Product, Engineering, Commercial, Finance, and Legal/Compliance- ensuring data serves every function from a shared, trusted foundation.
• Build a culture of data discipline — standardizing how information is captured and governed so insight is consistent, discoverable, and trusted across the organization.
•  Represent the data function at the executive level, partnering closely with the CTO and contributing to the broader AI and product roadmap.