Solutions Architect - AI & Data

Overview

The Head of Data Analytics will lead the airline's enterprise data and analytics function, with end-to-end accountability for data platforms, analytics delivery, and AI-enabled decisioning. The role requires deep airline domain expertise, strong data leadership, and the ability to scale analytics and applied AI capabilities across multiple business functions. This position is intended for a seasoned leader who has managed complex data organizations, built resilient data ecosystems, and embedded advanced analytics and AI into core airline operations and commercial processes.

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Role & Responsibilities

. Define and execute the enterprise data, analytics, and applied AI strategy aligned with airline business objectives

. Own the full lifecycle of data and analytics across ingestion, integration, modelling, analytics, and AI consumption layers

. Lead analytics and AI initiatives across:

o Revenue Management, Pricing, Forecasting, Network & Route Profitability

o Operations, IROPs, Fleet & Crew Optimization

o Customer, Loyalty, and Ancillary Revenue analytics

o Maintenance, Reliability, and Engineering analytics

. Architect and govern scalable data platforms supporting batch, streaming, and near real-time airline data

. Oversee development of advanced analytics and AI/ML models for forecasting, optimization, anomaly detection, and decision support

. Ensure AI-enabled insights and models are operationalized and embedded into airline workflows with appropriate controls

. Establish strong practices for data quality, observability, model governance, and responsible AI usage

. Lead, scale, and manage multiple teams across Data Engineering, Analytics Engineering, Data Science, and ML Engineering

. Build senior leadership capability within teams through mentoring, technical reviews, and outcome-driven delivery models

. Responsible for interacting with the CXO's of the organization in proving the value for Data and Analytics for the core business

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Required Skills

. 15-20 years of total experience, with minimum 10 years in senior data and analytics leadership roles

. Mandatory airline or aviation domain experience with strong understanding of commercial, operational, and engineering data

. Proven experience managing large, multi-disciplinary data organizations

. Strong expertise in enterprise data architecture and large-scale data platforms

. Experience delivering analytics and AI-enabled solutions in business-critical, regulated environments

. Ability to balance strategic leadership with hands-on architectural and analytical depth

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Must-Have Skills

. Demonstrated Airline Domain Expertise:

o Hands-on experience delivering data and analytics solutions within an airline or aviation environment

o Deep understanding of airline business processes, KPIs, and data across Revenue Management, Network Planning, Operations, IROPs, Fleet & Crew, Loyalty, and Maintenance

o Ability to translate airline operational and commercial challenges into scalable data and analytics solutions

. Hands-on leadership across Data Engineering, Advanced Analytics, and Applied AI

. Strong command over data modelling, analytical data products, and semantic layers

. Experience operationalizing predictive, forecasting, optimization, and anomaly detection models at enterprise scale

. Practical experience applying AI/ML techniques to enhance analytics-driven decision-making

. Exposure to Generative AI for analytics enablement, intelligent automation, or enterprise knowledge use cases

. Experience governing AI usage, model lifecycle management, and explainability in regulated environments

. Proven ability to lead and coordinate multiple teams and parallel workstreams across Data Engineering, Data Science, and ML Engineering

. Strong delivery governance with clear KPIs, outcome tracking, and measurable airline business impact

. Executive-level communication skills with the ability to challenge and influence senior airline leadership using data-backed insights