Descripción de la oferta
Overview
In this role you will define and drive data-driven and AI-powered solutions for Customer Operations, bridging business needs with data architecture and AI capabilities. You’ll shape the data vision, establish use cases and KPIs, and ensure scalable, high-impact outcomes that improve customer experience and operational efficiency. You will collaborate across data engineering, science, IT and business teams, translating requirements into concrete data products while upholding data governance and quality. This is a chance to influence how AI and graph-based data unlock value at scale in a leading European airline.
ResponsabilidadesOwn the data vision and roadmap for the business area, identifying data and AI opportunities to improve CX, efficiency and decision-makingTranslate business requirements into data and AI use cases with objectives, KPIs and prioritiesContribute to high-level data architectures, including sources, integration patterns, platforms, APIs and analytical layersDefine and drive AI and Generative AI use cases (LLMs for classification, summarisation, knowledge retrieval, automation, decision support)Explore Graph and Knowledge Graph-based use cases to connect entities and relationshipsCollaborate with Data Engineering, Data Science, AI, IT and business teams to ensure feasibility and scalabilityDefine business requirements and acceptance criteria for data products and intelligent solutionsEnsure data quality, governance and ownership across deployed solutionsMonitor performance and business impact of data and AI solutions for continuous improvementAct as a business reference point for Data & AI, communicating capabilities and opportunities of emerging tech
Requisitos principalesExperience translating business challenges into data requirements and AI/analytic solutionsStrong data literacy and ability to translate needs into clear data requirementsUnderstanding of data analytics and data-driven decision-makingKnowledge of modern data architectures (data lakes, data pipelines, APIs, cloud platforms)Understanding of Generative AI and LLMs and their business applicationsKnowledge of prompt engineering, RAG, embeddings and semantic searchUnderstanding of Graph and Knowledge Graph conceptsStrong analytical capabilities to identify patterns and impactFamiliarity with SQL and BI/analytics toolsAbility to understand and challenge technical solutions with stakeholdersStrong stakeholder management and communication skillsAbility to manage multiple data/AI initiatives by business valueExperience or exposure to Databricks, Microsoft Fabric, Snowflake, Power BI, Azure AI/OpenAI, vector DBs, Neo4j or related platformsExposure to data governance and data quality frameworksStakeholder managementClear communicationPrioritisation and time managementData architectures (lakes, lakehouses, pipelines, APIs)Generative AI and LLM conceptsPrompt engineering, RAG, embeddings, semantic search
