Enterprise Data and AI Integration Architect

World Vision

. Define and evolve the organization's target-state data, integration, analytics, and AI architecture .

Posted 9/15/2026full-timeUnited KingdomSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in defining and evolving data architecture, integration, and AI strategies, with a strong focus on governance, security, and compliance. Proven ability to connect business strategy with technology choices and lead enterprise-scale architecture decisions.

Highest-signal resume keywords

Data ArchitectureAI/ML ArchitectureCloud Data PlatformsEnterprise Architecture CertificationsSecurity and Compliance

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data IntegrationMachine LearningGenerative AIETL/ELTAPIsStreamingData QualityMetadata ManagementArchitecture Decision RecordsData Governance

Soft Skills

Influencing Senior StakeholdersFacilitating Cross-Functional DecisionsMentoring Technical TeamsResolving Ambiguity

Tools & Technologies

AWSAzureData LakeData WarehouseLakehouseEvent-Driven ArchitecturesOrchestration ToolsKnowledge GraphsSemantic TechnologiesData Mesh

Certifications & Qualifications

TOGAFOpen Group Certified Architect (Open CA)

Industry Keywords

Regulated IndustriesData-Sensitive EnvironmentsEnterprise Data CapabilitiesFinOpsAI Observability

Tech Stack

Tools & technologies

AWSAzureCloudETL

About the role

Key responsibilities & impact

Define and evolve the organization's target-state data, integration, analytics, and AI architecture
Connect business strategy to executable technology choices across data platforms, integration, information architecture, governance, analytics, machine learning, generative AI, and knowledge systems
Shape enterprise data and AI architecture strategy, principles, reference architectures, standards, models, and multi-year roadmaps
Assess current data estates, identify capability gaps and technical debt, and define target-state and transition architectures
Advise senior leadership on platform strategy, operating models, sourcing, build-versus-buy choices, vendor concentration, and fragmented data
Own Business, Data, Application, and Technology architecture for strategic solutions
Design end-to-end architectures, architecture building blocks, solution building blocks, and reusable patterns
Elicit business and functional requirements into implementable technical designs
Produce architecture artifacts, including solution overviews, diagrams, and architecture decision records, aligned with WVI methodology
Design scalable, resilient, and secure data architectures across cloud, hybrid, and multi-cloud environments
Define patterns for batch and real-time pipelines, ETL/ELT, change data capture, APIs, event-driven integration, streaming, data sharing, and interoperability
Guide data lake, warehouse, lakehouse, semantic, knowledge, and analytical serving layers
Define enterprise information models, domain boundaries, vocabularies, taxonomies, ontologies, and semantic models
Shape business-aligned data products with ownership, contracts, quality expectations, access policies, lineage, service levels, and lifecycle management
Architect AI-ready foundations for analytics, machine learning, generative AI, semantic search, knowledge graphs, retrieval-augmented generation, and agentic solutions
Define AI data preparation, feature and embedding pipelines, vector retrieval, model gateways, orchestration, evaluation, and deployment patterns
Embed governance, security, privacy, resilience, regulatory compliance, responsible AI, observability, and cost management into architecture
Define controls for least privilege, encryption, secrets management, data loss prevention, segregation of duties, audit logging, and AI-specific risks
Chair or contribute to architecture review boards and assure solution architectures, designs, data models, integration patterns, and vendor submissions
Maintain reference architectures, approved patterns, templates, guardrails, playbooks, and reusable building blocks
Prototype and technically validate high-risk architecture patterns through implementation, testing, migration, and production readiness
Resolve architectural issues and escalate cross-domain or high-impact matters to the Head of Enterprise Architecture
Track architecture adoption, outcomes, exceptions, technical debt, and improvement opportunities
Serve as trusted advisor to executives and build alignment across architecture, engineering, analytics, AI/ML, security, risk, product, and governance teams
Support portfolio planning, platform investment cases, vendor selection, delivery prioritization, and capability maturity assessments
Monitor technology and regulatory developments and introduce innovation with clear enterprise use cases
Act as a data architecture advisor to data owners, product teams, and governance forums

Requirements

What you’ll need

Bachelor's degree in Information Technology, Computer Science, Business, Enterprise Architecture, or a related discipline
Typically 10+ years of progressive experience across data architecture, data engineering, analytics platforms, enterprise architecture, or AI/ML architecture
At least 5 years leading enterprise-scale architecture decisions
Demonstrated ownership of current-state, target-state, and transition architectures for complex, multi-system data environments
Strong practical knowledge of modern cloud data platforms, lakehouse/warehouse patterns, data integration, serverless, MSA integration, event-driven architectures, integration modernization, APIs, streaming, orchestration, metadata, lineage, data quality, and master/reference data
Experience designing AI/ML or generative AI foundations, including production data pipelines, retrieval patterns, evaluation, deployment, observability, and governance controls
Cloud experience in AWS/Azure
Deep understanding of security, privacy, resilience, regulatory compliance, and responsible AI requirements in enterprise environments
Ability to translate business capabilities and non-functional requirements into architecture decisions, standards, roadmaps, and executable delivery guidance
Evidence of influencing senior stakeholders, facilitating cross-functional decisions, mentoring technical teams, and resolving ambiguity without formal authority
Excellent command of spoken and written English
Enterprise Architecture certifications such as TOGAF desirable
The Open Group Certified Architect (Open CA) certification preferred
Architecture experience in regulated or data-sensitive industries preferred
Experience building or materially modernizing enterprise data and AI capabilities preferred
Hands-on experience validating architecture through prototypes, reference implementations, design spikes, or production delivery leadership preferred
Experience with knowledge graphs, semantic technologies, agentic AI, data mesh/product operating models, FinOps, or AI observability preferred
Consulting or executive-advisory experience preferred
Candidates must be based in countries where World Vision International is legally registered to operate
Local applicants only

Benefits

Comp & perks

Local - Fixed Term Employee (Fixed Term) contract
Employment with World Vision International, an organization operating in nearly 100 countries
Opportunity to contribute to work transforming vulnerable children’s life stories
Mentorship or guidance opportunities for aspiring architects and other professionals