Senior Data Architect

Job Purpose

The incumbent report into the AI and Data management unit (“AI & Data unit”), that is accountable to the Director of the DTD. The other units and teams reporting to the DT Director include the Enterprise Architecture, Strategy & Planning unit, the Digital development and management unit, the Infrastructure & Security Team and the Global Service Desk and Endpoint Management team. Under the leadership of the Director, these units and teams serve as members of the global DTD management team, along with the CISO and Regional DT managers. The AI & Data unit is responsible to deliver greater value from IFRC’s data, and ensures the development and implementation of IFRC’s data and AI governance and strategy, in close collaboration with the IFRC’s Data Protection Office and through indirect management of data professionals in other departments.

Job Duties And Responsibilities

• Strategic Data Architecture & Platform Vision
  • Define and articulate the long-term data architecture vision aligned with IFRC's business strategy and humanitarian objectives.
  • Design comprehensive enterprise data architecture leveraging a medallion architecture (bronze/silver/gold zones) for optimal data organization and governance.
  • Establish architectural standards, principles, and patterns for data ingestion, processing, storage, access controls, and quality management.
  • Evaluate and recommend technology investments, infrastructure choices, and platform capabilities to support current and future organizational needs.
  • Develop a strategic data platform roadmap spanning 1-3 years with phased implementation, measurable milestones, and clear business value articulation.
  • Design scalable multi-region, multi-tenant platform architecture supporting diverse data domains, high-volume data processing, and real-time analytics.
  • Conduct regular architecture reviews and optimization, identifying opportunities for performance enhancement, cost reduction, and modernization.
• Team Leadership & Development
  • Lead, mentor, and develop the Data Platform DevOps Engineer and full-stack data engineering and report development team, fostering technical excellence and professional growth.
  • Establish clear role definitions, responsibilities, and expectations for team members, supporting career development pathways.
  • Create structured mentoring programs addressing both technical skill development and leadership competencies for high-potential team members.
  • Conduct technical interviews and participate in hiring to build a cohesive, skilled team aligned with architectural vision.
  • Foster a collaborative culture emphasizing continuous learning, innovation, quality, and adherence to architectural standards.
  • Balance hands-on technical work with leadership responsibilities, maintaining credibility while delegating appropriately.
  • Support the team with clear boundaries, autonomy, and creative problem-solving within governance frameworks.
• Platform Architecture & Design Leadership
  • Lead end-to-end system design for complex data solutions across Microsoft Fabric and Microsoft Azure platform components.
  • Makes critical technology selection decisions regarding Fabric items (Lakehouses, Warehouses, Data Factory, Power BI, Real-Time Intelligence), infrastructure, and tools.
  • Architect data quality frameworks, testing standards, and metadata management approaches ensuring consistency and reliability.
  • Guide implementation of complex data integration patterns between enterprise systems and external data sources.
  • Oversee system integration and ensure seamless communication between platform components, maintaining architectural coherence.
  • Establish patterns for scalability, performance optimization, disaster recovery, and business continuity.
• Governance & Standards Support
  • Work with data governance and compliance teams to establish architectural guardrails and ensure regulatory adherence.
  • Create comprehensive documentation standards for architecture decisions, technical designs, security controls, and operational procedures.
  • Define and monitor key performance indicators (KPIs) for data platform quality, reliability, performance, and cost.
  • Establish change management and governance processes for architecture reviews, platform evolution, and technology decisions.
• Platform Engineering & DevOps Leadership
  • Oversee design and implementation of CI/CD pipelines, infrastructure automation, and deployment strategies for Microsoft Fabric.
  • Sure platform engineering best practices including observability, monitoring, alerting, and incident response frameworks are implemented.
  • Guide the DevOps engineer in establishing platform maintenance procedures, capacity planning, and operational excellence.
  • Review and optimize platform infrastructure design, cost efficiency, and resource utilization strategies.
  • Sure disaster recovery and business continuity strategies are designed, tested, and maintained.
• Stakeholder Management & Communication
  • Develop and maintain stakeholder communication strategy aligned with organizational priorities and decision-making needs.
  • Create tailored architectural views for different stakeholder groups including executives, business units, and technical teams.
  • Present architectural recommendations and technical strategies to executive leadership, translating complex technical concepts to business impact.
  • Facilitate cross-functional collaboration between data platform team, data product teams, business units, and DT governance.
  • Drive organizational conversations on data strategy alignment and technical standards.
  • Establish clear communication cadences and channels for different stakeholder groups (executive updates, team briefings, documentation).
• Data Architecture Strategy & Roadmap Development
  • Contribute to overall organizational data strategy aligned with business objectives and humanitarian mission.
  • Define organizational capability building needs including platform enablement, team skill development, and process improvements.
  • Regularly reassess strategy based on evolving business needs, technological advancements, and lessons learned.
  • Monitor emerging technologies and industry trends in data platforms, architecture patterns, and analytics.
  • Foster a culture of continuous improvement, encouraging experimentation and calculated risk-taking within governance boundaries, supporting innovation.
  • Establish knowledge management practices capturing architectural decisions, lesson
  • establish knowledge management practices capturing architectural decisions, lessons learned, and best practices.