Manager Cargo iQ & Service Delivery

Synopsis

Responsible for the delivery of data‑driven insights that enable strategic and operational decision‑making. This role oversees analytics projects end‑to‑end, partners closely with business leaders, and manages a team of analysts. Works closely together with the Product Owner Cargo Data to productionize data and insights. You will be responsible for revenue budgeting and forecasting.

As Product Owner of IATA Cargo iQ and related quality standards: defining, prioritizing and evaluating the work related to the IATA Cargo iQ quality standard, the Delivered-As-Promised (DAP) performance indicator and customer and service specific standards.

Accountabilities

• Delivery of analytics insights aligned with business needs.
• Identify high‑value opportunities where data and insights can drive business impact.
• Produce the revenue budget and related materials at agreed intervals
• Produce the revenue forecast and related materials at agreed intervals
• Identify opportunities to productionize data and insights
• Accountable to maintain Etihad Cargo’s IATA Cargo iQ certification at all times, lead re-certifications and address any findings and observations to maintain compliance.
• Responsible for managing all cargo offsets, ensuring offsets are up-to-date and accurate at all times. This includes but is not limited to Cargo iQ offsets under CDMP, customer and service provider specific offsets under respective Service Level Agreements.
• Accountable for continuously improve data integrity of operational data and active engagement with internal and external stakeholders, creating awareness, transferring knowledge across cargo departments and further improve operational performance.
• Communicate effectively with all stakeholders, internally and externally.

Education & Experience

• Minimum 5 years relevant experience in airline or logistics, with at least 2 of these years in a supervisory/management capacity.
• Bachelor’s degree in Business Admin, Aviation, Information Systems, Engineering or equivalent is preferable
• Familiarity with predictive modelling, forecasting, and optimization techniques
• Excellent communication, organizational and time management skills