Senior Airline DataEng Developer

Overview

The Senior Data Engineer will be an integral member of theairline's Data & Analytics engineering function, responsible for designing,building, and maintaining robust data pipelines, analytics platforms, andAI-integrated software solutions. A strong foundation in airline domainknowledge is central to this role — the ability to understand airline businessprocesses, operational data, and commercial workflows is what drives thedevelopment of meaningful, fit-for-purpose software solutions rather than generictechnical outputs. The role requires strong software engineering fundamentalscombined with deep expertise in data engineering, analytics tooling, andapplied AI development. This position suits a technically seasoned developerwho has built scalable data systems, taken end-to-end ownership of analyticsproduct delivery, and written production-grade code that powersbusiness-critical airline operations and commercial processes.

Role & Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines supporting batch, streaming, and near real-time ingestion across core airline operational and commercial data sources, ensuring data is available, consistent, and fit for analytical and AI consumption
• Own the full software development lifecycle for airline data and AI products — from requirements analysis, technical design, and data modelling through to build, testing, deployment, and production support across operational and commercial domains
• Engineer and deliver AI-powered data products that embed predictive models, forecasting engines, anomaly detection, and optimization outputs directly into airline workflows
• Develop Generative AI and Agentic AI software components tailored to airline business challenges — from AI-assisted disruption management and intelligent querying of flight and passenger data, to automation of repetitive operational tasks across network, cargo, and ground operations
• Develop and optimize airline-domain data models, analytical data products, and semantic layers covering key business areas such as passenger revenue, yield, on-time performance, seat utilization, maintenance cost, and customer experience on cloud-native platforms
• Implement and maintain data quality frameworks, validation rules, and pipeline observability tooling suited to airline data characteristics — handling operational data spikes, schedule volatility, and high-frequency telemetry feeds
• Support migration and modernisation initiatives — transitioning legacy airline reporting systems and siloed operational data stores to unified cloud-native analytics and AI platforms
• Participate actively in code reviews, enforce development standards, and contribute to technical documentation and architectural decision records across the airline data and AI engineering team
• Collaborate closely with data scientists, ML engineers, revenue analysts, operations controllers, and business analysts to bridge the gap between airline analytical requirements and production-grade engineering delivery

Required Skills

• 15 to 18 years of total experience in data engineering, with significant depth in designing and delivering data pipelines, transformation logic, and analytics engineering solutions using Python, SQL in production environments
• Mandatory airline or aviation domain experience with strong working knowledge of commercial, operational, and engineering data — sufficient to independently translate business requirements into scalable data solutions
• Proven experience delivering end-to-end data products — covering pipeline development, data modelling, cloud platform deployment, and production support — in business-critical, regulated environments where reliability and data quality are non-negotiable
• Strong expertise in data architecture fundamentals — including dimensional modelling, star and snowflake schemas, Lakehouse patterns, and cloud-native platform development using AWS, Azure,