Senior Data Engineering Expert
Listed on 2026-06-25
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IT/Tech
Data Engineering
Senior Data Engineering Expert
We are seeking a highly experienced Senior Data Engineering Expert with deep expertise in the Airline IT domain to lead the design, development, modernization, and governance of enterprise‑scale data platforms and data integration ecosystems.
Key Responsibilities Enterprise Data Platform ArchitectureDefine and implement enterprise‑wide data architecture strategies supporting commercial, digital, customer, and operational business functions. Design scalable, resilient, and secure data platforms that enable analytics, reporting, machine learning, and operational decision‑making. Lead the modernization of legacy data environments toward cloud‑native Lakehouse architectures and enterprise data ecosystems. Establish data engineering standards, architectural principles, governance frameworks, and best practices across the organization.
Airline Business Data EnablementDesign and implement scalable enterprise data architectures supporting Airline Commercial and Digital functions, Reservations and Passenger Service Systems (PSS), Revenue Management and Pricing, Loyalty Programs, Customer Relationship Management (CRM), Customer Data Platforms (CDP), Digital Engagement and Mobile Applications, Customer Analytics and Personalization, Commercial Performance and Regulatory Reporting.
Data Engineering & Integration ArchitectureDevelop scalable data ingestion, transformation, and serving layers supporting both batch and real‑time processing requirements. Design reusable and metadata‑driven ETL/ELT frameworks capable of handling large volumes of transactional, operational, and customer data. Establish enterprise integration patterns leveraging APIs, event‑driven architectures, messaging technologies, and hybrid connectivity models. Implement data quality controls, reconciliation mechanisms, lineage tracking, metadata management, and observability capabilities. Drive automation of deployment, orchestration, monitoring, recovery, and operational support processes.
Real‑TimeData & Analytics
Design and implement streaming architectures that provide near real‑time operational visibility and business insights. Enable event‑driven data processing capabilities supporting customer engagement, disruption management, operational performance monitoring, and decision support. Ensure scalability, reliability, and performance of real‑time data processing platforms.
Data Management & GovernanceEstablish enterprise Master Data Management (MDM) strategies and governance frameworks. Define and govern master data domains including customers, flights, airports, aircraft, crew, and enterprise reference data. Drive data stewardship, golden record management, metadata governance, and enterprise data quality initiatives. Ensure compliance with security, privacy, regulatory, and corporate governance requirements.
Leadership & Stakeholder ManagementProvide technical leadership and direction across data engineering and architecture teams. Mentor engineers, architects, and technical leads while fostering a culture of engineering excellence. Collaborate closely with business stakeholders, product owners, enterprise architects, airline operations teams, and executive leadership. Lead strategic modernization, cloud transformation, and enterprise data platform initiatives.
Required Qualifications & Technical ExpertiseBachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline. Experience in data engineering, data architecture, data platform engineering, or enterprise data management roles. Proven experience delivering enterprise‑scale data platforms within complex and highly integrated environments, preferably in the airline, aviation, travel, or transportation industry. Extensive expertise in designing and implementing modern cloud‑based data architectures using Microsoft Azure and Databricks Lakehouse technologies.
Strong hands‑on experience building scalable data engineering solutions leveraging Spark, Scala, Spark SQL, Delta Lake, and modern orchestration frameworks to support both batch and real‑time workloads. Demonstrated success in developing…
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