Senior Director, Enterprise Data Management

🏢 Versapay · all 12 jobs
📍 United States
💰 USD 180,000 - 220,000 / annual
📅 Posted Sep 13, 2026 · via Himalayas
🏷 Data Management, Enterprise Data Management, Data Strategy, Data Governance, Data Architecture, Enterprise Data Strategy Director +2 more
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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.
What You’ll Do

Data Strategy & Architecture

- 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.

Data Governance & Quality

- 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.

AI Enablement & Agentic Readiness

- 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.

Data Accessibility & Commercialization

- 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.

Team Leadership

- Lead and grow the Data Platform Team, building a high-performing function with clear ownership across data strategy, engineering, consumption, AI compute; in tight part

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