Job Description

Employment Type: Permanent
Contract Duration:

Why you will love working here

At IATA, we represent over 350 airlines worldwide, striving to make
aviation safer, smarter, more sustainable, and inclusive.

• Our Values are not just words on a page - they are the energy behind everything we do: ONE IATA - We collaborate across teams, TRUSTED - We do the right thing, INNOVATIVE - We make tomorrow better, INCLUSIVE - We embrace diverse perspectives.
• With over 30,000 courses available, we believe in continuous learning and support your growth in an ever-changing industry.
• Diversity, equity, and inclusion are our priorities. We are certified by the Equal Salary Foundation, offering equal pay and family-friendly policies.
• We encourage community involvement through volunteering and strive to make tomorrow better for aviation and our communities. We offer time off so you can support causes important to you.
• We promote work-life balance with flexible work options, including remote and hybrid work, a generous 'work from abroad' policy, and you get your birthday off!

About the team you are joining

Part of the Information and Data (I&D) Division, the Senior Data Architect & Data Modeler function is responsible for defining, maintaining, and evolving IATA’s data assets, standards, and practices across the organisation and with external industry stakeholders.

The team ensures consistency and interoperability between enterprise data models, industry standards, and implemented data solutions, supporting IATA’s ambition to make data accessible, trusted, and actionable across all business domains.

About the role

Reporting to the Senior Manager, Data Architecture and Modelling, the Senior Data Architect & Data Modeler is responsible for designing and maintaining data models and end-to-end data solutions across enterprise, industry, and system landscapes.

The role covers enterprise data modelling, industry-aligned data structures, and contribution to data solution design, ensuring that data is consistently defined, structured, and implemented across platforms.

The role acts as a key bridge between business requirements, data architecture, and technical implementation, ensuring alignment between conceptual models and physical solutions, including data pipelines, integration layers, and AI-driven interaction models.

What your day would be like

You will design and evolve data models and data solutions supporting operational systems, analytics platforms, data integration, and AI-enabled use cases.
You will collaborate with business stakeholders, architects, engineers, and external partners to ensure alignment between enterprise standards, industry models, and implemented solutions.

• Design and maintain conceptual, logical, and physical data models across enterprise, industry, and solution domains
• Translate business and industry requirements into scalable, standardised, and interoperable data structures
• Define and support data pipelines, integration patterns, and data flows (ETL/ELT)
• Ensure alignment between enterprise models, industry standards, and system implementations
• Design and support AI-ready data structures, semantic layers, and data products for analytics and AI use cases
• Define data structures and contracts supporting APIs, AI agents, and MCP-based data interaction models
• Apply data modelling, governance, and quality standards across all solutions in collaboration with architects, engineers, and business teams.

We would love to hear from you if

• 7+ years of experience in data modelling across enterprise and/or industry data domains
  
• Strong expertise in conceptual, logical, and physical data modelling
  
• Proven ability to translate business and industry requirements into standardised, scalable data solutions
  
• Experience with data integration, pipelines, and ETL/ELT processes
  
• Good understanding of data architecture and cloud data platforms (e.g. AWS, Snowflake)
  
• Experience with APIs, data contracts, and AI/semantic layer concepts (e.g. MCP, agent-based interactions, or similar)
  
• Strong stakeholder management and communication skills
  
• Experience designing AI semantic layers, knowledge models, or data products for AI consumption
  
• Exposure to MCP or comparable frameworks for AI orchestration and structured data interaction
  
• Knowledge of data governance, metadata, and data quality practices
  
• Experience with modelling tools (e.g. Sparx EA or similar)

Travel Required: 10-15