Advanced Analytics Engineer

This role leads the responsible adoption, governance and practical delivery of artificial intelligence, advanced analytics and intelligent automation across Plan International’s data and reporting landscape. It translates organisational priorities into high-value AI and analytics use cases that are grounded in trusted data, clear business definitions, responsible AI principles and measurable outcomes.

Responsibilities

• Define and maintain practical AI governance standards, Copilot, data agents and AI-assisted decision support.
• Ensure AI and advanced analytics use cases follow human-in-the-loop, transparency, accountability, privacy and security principles.
• Assess and prioritise AI use cases based on business value, data readiness, risk, feasibility and organisational capacity.
• Develop minimum standards for AI solution documentation, prompt design, evaluation, testing, approval and ongoing monitoring.
• Coordinate with Data Governance, Privacy, Information Security, Risk and Internal Audit to ensure AI solutions are responsibly controlled.
• Maintain an AI and advanced analytics use-case register, including ownership, data sources, controls, benefits, risks and lifecycle status.
• Support responsible adoption of Microsoft Copilot, Copilot Studio, Fabric data agents and related AI capabilities in line with organisational guardrails.
• Promote practical AI governance that balances innovation, user empowerment, safeguarding, compliance and operational control.
• Establish governance standards for AI-ready metadata so AI and Copilot experiences are grounded in authoritative, well-structured and properly labelled content.
• Establish AI risk management processes including impact assessments, model and tool inventories, approval workflows, testing criteria, incident response, audit evidence and periodic review.
• Monitor relevant AI regulation, standards and good practice, including risk-based AI governance frameworks, privacy requirements and sector-specific ethical obligations affecting humanitarian and development work.
• Design and enable advanced analytics solutions using Microsoft Fabric, Power BI, Snowflake, DBT, SQL and approved enterprise data sources.
• Strengthen semantic models, measures, business definitions and metadata so AI-generated insights are grounded in trusted analytics logic.
• Support development of natural-language analytics, Copilot-enabled reporting, data-agent experiences and AI-assisted insight discovery.
• Create prototypes and proofs of concept for AI-enabled analytics, ensuring clear evaluation criteria before broader adoption.
• Work with technical teams to connect AI solutions to governed data sources while preserving access controls, lineage and security.
• Define and maintain metadata and ontology requirements for AI-enabled analytics, including SharePoint managed metadata, content types, business taxonomy, Microsoft Fabric ontology, OneLake catalog metadata, Power BI semantic model descriptions, glossary terms, tags, relationships, synonyms and data-agent grounding instructions.
• Work with SharePoint owners, data product owners and governance stakeholders to improve metadata quality, ownership, access control, source-of-truth clarity and discoverability for AI-assisted search, reporting and insight generation.
• Ensure AI and advanced analytics products include clear ownership, documentation, support model, quality checks and change controls.
• Define evaluation methods for AI-assisted analytics, including accuracy checks, hallucination testing, bias and fairness review, usability testing, model or prompt performance monitoring and clear criteria for moving prototypes into production.
• Partner with data engineering and architecture teams to ensure AI solutions are production-ready, scalable, cost-aware, resilient and integrated with approved enterprise platforms and security controls.
• Develop guidance, playbooks and training materials for responsible use of AI, Copilot and advanced analytics across Plan International.
• Deliver enablement sessions, clinics and communications that help business users understand what AI can safely support and where controls are required.
• Support stakeholder engagement for AI initiatives, ensuring expectations are realistic and business adoption is planned from the start.
• Coordinate with vendors and implementation partners by reviewing AI-related deliverables, technical designs and governance implications.
• Communicate AI capabilities, limitations, risks and benefits in clear language for global business and technical stakeholders.
• Curate and maintain AI and advanced analytics resources, including templates, use-case guidance, evaluation checklists and lessons learned.
• Promote consistent and responsible AI ways of working across the global network through practical standards and reusable assets.
• Monitor emerging trends in Microsoft Fabric, Power BI, Copilot, AI agents, responsible AI, analytics engineering and data governance.
• Provide thought leadership on how Plan International can safely scale AI-enabled analytics while maintaining trust, accountability and value.
• Track and report value delivered by AI and advanced analytics initiatives, including adoption, time saved, quality improvement, risk reduction, user satisfaction and benefits realised.
• Ensures that Plan International’s global policies for Safeguarding Children and Young People and Gender Equality and Inclusion are fully embedded in accordance with the principles and requirements of the policy including relevant Implementation Standards and Guidelines as applicable to their area of responsibility.

Requirements

• Proven experience in Information Systems, Computer Science, Data Science, Information Management or a related field.
• Experience in AI enablement, advanced analytics, data governance, analytics engineering or BI transformation.
• Hands-on experience with enterprise data and analytics platforms such as Microsoft Fabric, Power BI, Snowflake, DBT, SQL, Python, Power Automate or Copilot.
• Strong understanding of semantic models, metadata, business definitions, data lineage and analytics quality controls.
• Ability to translate business needs into governed AI, analytics and automation use cases with clear success criteria.
• Knowledge of responsible AI principles, including transparency, human oversight, fairness, privacy, ethical use, security and accountability.
• Practical understanding of AI risk controls, including secure access, data protection, vendor assurance, output evaluation, monitoring and incident escalation.
• Strong communication, facilitation and stakeholder management skills in a global, multicultural environment.
• Ability to move from concept to prototype, testing, documentation and adoption.
• Professional certifications or training in AI, data science, Microsoft Fabric, Power BI, Snowflake, DBT, data governance or responsible AI (desirable).
• Experience working in the international development, NGO, or humanitarian sector (desirable).
• Experience with Azure AI Foundry, Copilot Studio, Fabric data agents, Azure OpenAI, AI Builder, Model Context Protocol (MCP), machine learning, Python or notebook-based analytics (desirable).
• Experience supporting change, release management, user adoption and governance for AI or analytics products (desirable).
• Experience with regulatory or standards-based AI governance approaches such as NIST AI RMF, ISO/IEC 42001, data protection impact assessments or equivalent organisational risk frameworks (desirable).

Skills

• Computer Information Systems
• Computer Science
• Data Science
• Information Management
• AI Enablement
• Applied Analytics
• Data Governance
• Analytics engineering
• BI Transformation
• Microsoft Fabric
• Power BI
• Snowflake
• dbt
• SQL
• Python
• Power Automate
• Copilot Agent
• Semantic Models
• Metadata Management
• Business Definitions
• Data Lineage
• Analytics Quality Controls
• Governed AI Use Cases
• Responsible AI Principles
• AI Risk Controls
• Secure Access
• Data Protection
• Vendor Assurance
• Output Evaluation
• Monitoring and Incident Escalation
• Stakeholder Management
• Prototype Development
• Documentation
• AI Certifications
• Azure AI Foundry
• Copilot Studio
• Fabric Data Agents
• Azure OpenAI
• AI Builder
• Model Context Protocol
• Machine Learning
• Notebook-based Analytics
• Change Management
• Release Management
• User Adoption Support
• AI Governance
• NIST AI RMF
• ISO IEC 42001
• Data Protection Assessment

Languages

English