Data Analytics Officer

Job Description Synopsis: The Service Innovation Data & Analytics Officer is the data backbone of the Service Innovation portfolio within Product & Hospitality. The role turns operational, guest and service data from OCR forms, NPS / verbatim surveys, Skypad, Panasonic IFEC, catering systems and culinary planning tools into trusted datasets, Power BI products and AI-driven insights that leadership, Product, Brand and Hospitality teams can act on. The role combines three skill sets: data engineering (pipelines, modelling, refreshes), business intelligence (Power BI, DAX, storytelling) and applied AI (LLM-driven classification, summarisation and analysis acceleration), with growing fluency in aviation taxonomies (cabin classes, route/network structure, IATA NPS pillars, ATA references). Accountabilities: Power BI & Reporting Build and maintain Power BI dashboards across the portfolio: NPS / OCR, catering performance, Skypad usage, F&B KPIs, IFE / connectivity, menu compliance and project performance. Own data models, DAX measures, row-level security, refresh schedules and report documentation. Translate stakeholder questions into clear, decision-grade visuals; iterate based on user feedback. 2. Data Engineering & Pipelines Engineer and automate data pipelines from Panasonic, Skypad / Comply 365, OCR Power Apps, catering systems and NPS feeds. Apply Power Automate, Python and basic cloud tooling (Azure / Fabric where available) to clean, model and standardise inputs. Maintain a single source of truth for portfolio reporting governed, documented, version-controlled. 3. NPS, OCR & CX Deep-Dives Lead thematic analysis of NPS verbatims and OCR submissions; produce pillar-level reports for the NPS Workgroup (Crew, F&B, Airport, Technical). Maintain and evolve the CX taxonomy in line with airline cabin product classifications and IATA NPS pillars. Surface anomalies, recovery trends and product issues with structured recommendations. 4. Applied AI for Analytics Use generative AI tooling (Copilot, ChatGPT, Python LLM SDKs) to accelerate analysis: auto-classify feedback, summarise large datasets, draft executive narratives, generate DAX / SQL snippets. Build lightweight prompt-based or agentic workflows where they create durable leverage; ensure human review of all outputs. Stay current on AI tooling for analytics and propose practical applications. 5. Stakeholder Partnership Partner with project leads (NPS Workgroup, Catering Performance, Skypad, FWB, Menu Planner, Etihad Excellence) to shape analytical workstreams. Present findings clearly to the Service Innovation Manager, the Manager Strategic Digital Projects and when called upon the VP and Steer Co audiences. Provide quick training and documentation so dashboards and datasets are self-serve where possible. 6. Data Governance Maintain central documentation: definitions, owners, refresh frequency, lineage, access lists. Ensure changes are auditable, traceable and aligned with corporate data, security and privacy standards.