Senior Data Governance & Responsible AI Lead

About Sand Sand Technologies is a global Physical AI company using data and AI to make critical industries work better. We partner with governments, cities and enterprises to improve how essential systems operate across healthcare, water, energy, telecommunications and infrastructure. Our work delivers proven real-world impact. We have built AI systems that help manage London’s water supply, supported telecom network planning across hundreds of cities, and developed digital healthcare platforms serving tens of millions of people across Africa. From intelligent command centers to AI-powered infrastructure platforms, we help organizations sense, analyze and act in complex environments. Our people are ambitious, curious and relentlessly practical. Our teams work alongside clients in the field, solving hard problems and deploying solutions that last. With colleagues across Africa, Europe, the UK and the US, we operate across the full stack - from research and engineering to deployment and capability building. Our mission is simple: to harness AI to solve humanity’s most pressing challenges. About the role Sand Technologies is seeking a Senior Data Governance & Responsible AI Lead to establish and operationalize the governance foundation for the Baltimore Intelligence Center. This role is critical to ensuring the city’s data and AI ecosystem is governed with clear ownership, trusted metrics, operational controls, visible lineage, responsible AI practices, and production-ready governance processes. The successful candidate will lead governance implementation across the BIC program, working closely with city leadership, BCIT/security, legal stakeholders, platform engineering, data engineering, product teams, and agency data owners. This is a hands-on leadership role focused on operationalizing governance — not simply defining policy. The role will be responsible for establishing governance workflows, stewardship practices, AI governance processes, metadata standards, KPI governance routines, auditability controls, and governance reporting required to support production intelligence products and long-term city ownership. What you’ll do Lead Operational Data Governance Lead implementation and operationalization of the BIC governance framework across data, analytics, and AI products. Establish governance workflows for data ownership, stewardship, approvals, escalation paths, and auditability. Ensure governance processes are embedded into day-to-day delivery and operational decision-making. Coordinate governance activities across city agencies, OPI leadership, and delivery teams. Govern Source-System Readiness & Stewardship Lead governance readiness processes for datasets entering the BIC platform. Ensure priority datasets have named owners and stewards, approved access pathways, documented refresh cadences, lineage visibility, quality expectations, and operational governance controls prior to production use. Partner with agency stakeholders and technical teams to resolve governance and operational readiness gaps. Lead Metadata, Catalog & Lineage Governance Establish governance standards for metadata, lineage, business glossary, and catalog completeness. Support operational governance of enterprise metadata capabilities and data catalog processes. Ensure lineage and ownership are visible across source systems, platform layers, semantic assets, and intelligence products. Partner with engineering teams to improve transparency, traceability, and trust in the city’s data ecosystem. Own KPI & Semantic Governance Processes Lead governance processes for KPI definitions, semantic consistency, and business metric approval. Ensure intelligence products use standardized and approved definitions across domains and agencies. Partner with analytics, semantic-layer, and product teams to operationalize governance of business logic and reporting standards. Ensure production KPIs are documented, reviewed, governed, and aligned to approved definitions. Operationalize Responsible AI Governance Lead governance workflows for AI-enabled use cases and intelligence products. Manage governance processes including use-case intake, risk tiering, privacy and security review coordination, human-in-the-loop controls, logging and traceability expectations, and post-launch governance monitoring. Help ensure AI-enabled products are governed with appropriate transparency, oversight, and operational controls. Lead Governance Reporting, Quality & Audit Readiness Establish governance reporting, operational scorecards, and governance review routines. Partner with technical teams to define governance expectations for data quality, monitoring, and issue escalation. Ensure governance processes support auditability, inspectability, and public-sector accountability requirements. Support governance reviews for public-facing or operationally sensitive intelligence products. Drive Capability Transfer & Sustainability Develop governance playbooks, templates, SOPs, and operational documentation. Partner with OPI staff to transition governance capabilities into sustainable city operations. Help establish long-term governance routines that can operate independently following the initial implementation period. Who you are 8+ years of experience in data governance, information governance, analytics governance, enterprise data management, or related leadership roles. Proven experience operationalizing governance in complex, cross-functional environments. Strong knowledge of data ownership and stewardship, metadata and lineage, governance operating models, data quality, auditability, and governance controls. Experience working with cloud-based data and analytics platforms. Ability to work effectively across technical teams, business stakeholders, legal/security partners, and executive leadership. Strong facilitation, stakeholder management, communication, and documentation skills. Preferred experience Experience in government, civic technology, public-sector, healthcare, infrastructure, transportation, or other regulated environments. Experience with responsible AI governance, AI-enabled operational systems, or AI risk management practices. Familiarity with metadata and catalog platforms such as OpenMetadata, Purview, Collibra, Alation, or similar technologies. Working familiarity with governance and regulatory frameworks such as NIST, CJIS, HIPAA, SOC 2, or FedRAMP-related environments. Experience supporting KPI governance, semantic governance, business glossary management, or enterprise reporting standards. What Success looks like Success in this role includes establishing governance practices that are operational, scalable, and sustainable across the Baltimore Intelligence Center. By the end of the initial engagement, the program should have: Operational governance processes embedded into delivery workflows. Named ownership and stewardship for priority datasets. Governed KPI and semantic review processes. Operational AI governance and risk review workflows. Visible metadata and lineage standards. Governance scorecards and reporting routines. Governance practices that city teams can sustain independently over time. How we work Due to the highly collaborative and internationally distributed nature of our work, successful candidates must be comfortable operating in small teams while contributing to larger, globally coordinated efforts. A strong sense of ownership, self-motivation and discipline in maintaining clear and consistent communication through virtual collaboration tools and video conferencing is essential.