Vueling est une compagnie aérienne qui assure des vols de passagers en Europe et autour du bassin méditerranéen.
Data Business Owner
At Vueling, we connect people, places and opportunities ✈️ As part of the IAG Group, we are one of Europe’s leading airlines, serving around 250 routes across 30 countries and welcoming millions of customers every year. With more than 5,000 employees, Vueling is the only European airline recognized as a Top Employer for three consecutive years. Driven by in…
Repères sur Vueling
- Domaine officiel
- vueling.com
- Offres ouvertes
- 22
Détails de l’offre
La description complète publiée par Vueling.
At Vueling, we connect people, places and opportunities ✈️ As part of the IAG Group, we are one of Europe’s leading airlines, serving around 250 routes across 30 countries and welcoming millions of customers every year. With more than 5,000 employees, Vueling is the only European airline recognized as a Top Employer for three consecutive years. Driven by innovation, collaboration, and a commitment to sustainability, we are shaping the future of aviation while creating an environment where our people can grow, contribute, and make an impact.
Mission We are looking for a Data Business Owner to lead the definition, development and evolution of data-driven and AI-powered solutions within Customer Operations. The role will act as the bridge between business needs, data architecture, analytics and Artificial Intelligence, ensuring that data is transformed into actionable insights and scalable intelligent capabilities. The successful candidate will combine strong business understanding with solid knowledge of data and AI concepts.
Deep engineering expertise is not required, but the person should be comfortable discussing data architectures, integration models, analytics, LLM-based solutions and graph-based data relationships with technical teams. Tasks & Responsibilities
- Own the data vision and roadmap for the business area, identifying opportunities where data and AI can improve customer experience, operational efficiency and decision-making.
- Translate business requirements into data and AI use cases, defining objectives, expected outcomes, KPIs and priorities.
- Contribute to the definition of high-level data architectures, including data sources, integration patterns, data platforms, APIs, analytical layers and consumption models.
- Define and drive AI and Generative AI use cases, particularly solutions based on Large Language Models for classification, summarisation, knowledge retrieval, intelligent automation and decision support.
- Explore use cases based on Graph and Knowledge Graph technologies, connecting customers, interactions, transactions, behaviours and other entities through relationship-based data models.
- Collaborate with Data Engineering, Data Science, AI, IT and business teams to ensure solutions are technically feasible, scalable and aligned with business priorities.
- Define business requirements and acceptance criteria for data products and intelligent solutions.
- Ensure appropriate data quality, governance and ownership across the solutions under their responsibility.
- Monitor the performance and business impact of deployed data and AI solutions, identifying opportunities for continuous improvement.
- Act as a business reference point for Data & AI, helping stakeholders understand the capabilities, limitations and opportunities of emerging technologies. Academic Background
- Bachelor’s degree in Business, Data, Technology, Engineering, Computer Science, Mathematics or a related field.
- Additional training or certifications in Data Analytics, Artificial Intelligence, Data Architecture or Data Governance will be considered an advantage. Experience
- Experience translating business challenges into data requirements and analytical or AI solutions.
- Strong data literacy, with the ability to understand and interpret complex datasets and translate business needs into clear data requirements that enable reliable analytics and insights.
- Strong understanding of data analytics and data-driven decision-making.
- Good high-level knowledge of modern data architectures, including data lakes, lakehouses, APIs, data pipelines, cloud data platforms and analytical layers.
- Understanding of Generative AI and Large Language Models and their application to real business use cases.
- Knowledge of concepts such as prompt engineering, RAG, embeddings and semantic search.
- Understanding of Graph and Knowledge Graph concepts, including entities, nodes, relationships and their application to complex datasets.
- Strong analytical capabilities and the ability to identify patterns, opportunities and potential business impact through data.
- Familiarity with SQL and BI or analytics tools. Advanced software engineering skills are not required, but the candidate should be able to understand and challenge technical solutions.
- Strong stakeholder management and communication skills, with the ability to work effectively with both business and technical teams.
- Ability to manage and prioritise multiple data and AI initiatives according to their business value.
- Experience or exposure to technologies such as Databricks, Microsoft Fabric, Snowflake, Power BI, Azure AI, Azure OpenAI, vector databases, Neo4j or other LLM and Knowledge Graph platforms.
- Exposure to data governance, data quality frameworks and RAG architectures will also be valued. 💛 Vueling Values Our values are what we believe in, what we stand for and how we behave. - Make it happen - Make it better - Make it safe - Make it cost-focused - Make it customer-oriented - Win together Vueling is committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other status.
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