Digital & Data Transformation Expert

Agri Data Platforms, DecisionSupport, and Digital Role purposeDefine and deliver the digital and data backbone required to execute the agriculture transformation: registries, integrated data platforms, analytics/AI use cases, and decision support tools—ensuring governance, interoperability, cyber/privacy compliance, and adoption.Responsibilities:Digital transformation strategy(within agriculture)Define the digital visionand target architecture aligned to transformation priorities:Farmer/farm registryand identityLand and production dataSubsidy administration and compliance workflowsBiosecurity/food safety traceability where relevantTranslate transformation initiatives into a digitalroadmap with sequencing and dependencies.Data governance and operating modelEstablish agriculture data governance:Data ownership and stewardship modelData qualitystandards, master data rules, metadataAccess controlsand privacy complianceDefine interoperability standards with other entities (finance, customs, utilities, environment, municipalities).Ensure integration of the data with core government systems (land registries, statistical systems etc.)Define data acquisition strategies, including external partner data.Platform and productdeliveryDefine requirements and lead deliveryfor core platforms(as product owner or technical lead):Integrated Agriculture Data Platform (datalake/warehouse, APIs)Case management systems (subsidies, inspections, farmer services)Dashboards for executive monitoring (TMO portfolio + sector KPIs)Oversee system integrators/vendors: scope,delivery milestones, acceptance criteria, and operational handover.Advanced analytics and decision supportIdentify and prioritize high-value analytics/AI use casestied to operational decisions:Water use efficiency and anomaly detectionYield estimation and forecasting (where data allows)Targeting and fraud/leakage detection for subsidy schemesDisease/pest surveillance analytics (where relevant)Establish MLOps/analytics lifecycle standards where AI is used.Adoption and capability transferBuild digitalcapability within the entity:Product management disciplineAnalytics literacyfor business ownersTraining and “train-the-trainer” programsEnsure operational sustainability: SLAs, supportmodel, change releases.Required experience and qualifications.Education: Bachelor’s degree in computer science, data engineering, systems engineering, or equivalent; advanced degree preferred.10+ years in digital/data transformation, with at least 3–5 years in agriculture/food systems, environment/resource sectors, or adjacent public sector domains.Experience delivering platforms (not just strategy): registries, data platforms, workflow systems.Strong understanding of government compliance requirements (data privacy,cyber, procurement).