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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director of Enterprise Data Management - **Company:** Lever, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $180,000.0 - $220,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Software as a Service, Cloud Database, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Sharing, Data Warehousing, Role-Based Access Control, Data Streaming, Enterprise Data Management, Business Intelligence Development Studio, Large Language Models, Snowflake, Data Strategy, Data Layers, Real Time Data, Data Management, Machine Learning Operations, Data Objects - **Published:** September 12, 2026 - **Apply:** https://jobs.lever.co/versapay/37be53bb-2a2a-40e2-914e-f2f6ff9cd339/apply ## About the Role * 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. ## Description 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [Architectures that we can use with .NET](https://www.wearedevelopers.com/videos/935-architectures-that-we-can-use-with-net) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)