高级总监，企业数据管理
Senior Director, Enterprise Data Management
关于Versapay
Versapay是重新定义应收账款的平台，通过消除收集和对账B2B支付的障碍，提供端到端的现金流透明度，确保企业可以按自己的方式管理营运资金。通过将财务团队及其业务系统、客户和支付活动整合到一个智能生态系统中，Versapay将资金问题转化为数据驱动的优势。目前有10,000名客户和500多万家公司进行交易，Versapay每年处理超过1.1亿笔交易，处理的支付金额超过3000亿美元。
关于该职位
我们正在寻找一位具有战略眼光、擅长构建的高级企业数据管理总监，在我们发展的重要时刻负责并执行Versapay的企业数据战略。这位领导者将推动我们的交易数据、运营数据、行为数据、关系数据和意图数据层的融合，形成统一的运营基础架构——这是实现AI驱动产品功能、语义数据模型、外部化数据产品和自主应收账款流程的基础。
这是一个高可见度、高影响力的职位，直接与我们的产品和商业路线图相关，并有明确的指令和高管支持。
你将负责的工作
数据策略与架构
- 定义并推动Versapay的企业数据策略，将数据路线图与产品、AI和商业目标对齐。
- 领导将我们的交易数据、运营数据和分析数据层整合为统一的双向运营基础架构。
- 主导一个多年的数据成熟度路线图，在架构、语义、治理和可访问性方面设定清晰的里程碑。
- 推崇以业务为导向的数据建模理念：标准层次结构、企业本体论和共享指标目录，使人类和AI代理能够一致地解释数据。
数据治理与质量
- 将数据治理作为首要事项进行操作——自动化分类、基于角色的访问控制（RBAC）执行、平台服务级别协议（SLA）和认证数据对象。
- 建立企业数据目录，用可搜索、自助式发现层取代机构知识。
- 部署并维护高管数据健康仪表盘，持续监控数据资产的健康状况和完整性。
- 强制执行数据采购门禁，确保新工具和系统在进入资产前经过审查和分类。
- 建立并拥有企业数据资产注册表，以实现数据资产的管理
查看英文原文
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 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.
What You Bring
Required
• 10+ years of experience in data leadership, with at least 5+ years at the Director level owning enterprise data strategy, architecture, or governance.
• Demonstrated track record of modernizing and unifying complex, multi-source data environments at scale — ideally in a SaaS, fintech, payments context.
• Deep expertise in modern data stack: cloud data warehouses (Snowflake preferred), lakehouse architectures, ETL frameworks, and semantic/canonical modelling.
• Strong evidence of application of AI and ML infrastructure — including how data governance, observability, and semantic standards underpin safe, scalable AI deployment.
• Proven ability to build and lead high-performing technical teams and partner effectively across Product, Engineering, and Commercial functions.
• Experience governing data for commercial use: external data products, consent frameworks, lineage standards, and privacy compliance.
• Exceptional communication skills — able to translate complex data and architectural concepts for executive audiences and build alignment across functions.
• Experience with managing the cost of data warehouses and cost forecasting.
• Experience in hiring and managing talent across the entire data food chain – from BI and Analytics to Data Engineering to CI/CD of data platforms.
Preferred
• Experience with agentic AI architecture, MCP, or LLM serving layers and the data requirements that underpin them.
• Familiarity with AR/AP automation, payments, or working capital platforms and the data models they generate.
• Track record of commercializing data as a product — packaging data assets, building external APIs, or creating data-sharing programs with partners.
• Experience managing data maturity transformations with structured roadmaps, measurable milestones, and executive visibility.
• Hands-on experience with AWS-native data infrastructure (Glue, SageMaker, Bedrock) alongside Snowflake and modern BI tooling.
• Background in a PE-backed, high-growth SaaS environment.