A travel company is now competing for engineers the way universities compete for students.
En los márgenes de la industria del viaje, una empresa española ha cruzado silenciosamente hacia un territorio reservado a los gigantes tecnológicos: eDreams ODIGEO, con sede en Madrid, contrató a 400 personas de entre casi 29.000 candidatos el año pasado, alcanzando una tasa de aceptación del 1,4% que rivaliza con las universidades más selectivas del mundo. Lo que atrae a los ingenieros no es la marca, sino la infraestructura —un sistema de inteligencia artificial que procesa más de 100 millones de búsquedas diarias y genera 6.000 millones de predicciones automatizadas cada día. En un momento en que el talento tecnológico se ha convertido en el recurso más escaso del siglo, esta empresa de suscripciones de viaje plantea una pregunta más profunda: ¿puede una compañía redefinir su propia naturaleza simplemente por la calidad de las personas que elige?
- Con una tasa de aceptación del 0,98% sobre el total de candidaturas, eDreams ODIGEO es hoy más selectiva que Harvard, lo que señala una transformación radical en cómo las empresas de viaje compiten por el talento global.
- La tensión es real: una compañía de suscripciones de viaje se mide ahora en el mismo mercado de talento que Apple, Netflix y Microsoft, y el mercado, por ahora, le da la razón.
- La inversión en formación casi se duplicó en un año —de 48.933 a 99.335 horas anuales—, con foco en competencias de IA, mientras la IA agéntica ha elevado la productividad de ingeniería un 47%.
- La retención acompaña al reclutamiento: la rotación voluntaria cayó un 14% en el ejercicio fiscal 2026 y la antigüedad media creció un 6%, señales de que la selectividad no es solo una estrategia de imagen sino de construcción a largo plazo.
- El horizonte apunta a 13 millones de miembros en Prime para 2030, con equipos concentrados en Barcelona, Madrid, Oporto y Milán desarrollando los modelos de personalización que sostendrán esa ambición.
eDreams ODIGEO, la mayor empresa de suscripciones de viaje del mundo, contrató el año pasado a 400 profesionales de entre casi 29.000 candidatos, lo que arroja una tasa de aceptación del 1,4%. Si se considera el total de candidaturas —más de 40.000—, esa cifra cae al 0,98%, por debajo de la tasa de admisión de Harvard. La comparación no es casual: una empresa con sede en Madrid compite hoy por ingenieros del mismo modo en que las universidades de élite compiten por estudiantes.
Lo que atrae a ese talento no es el prestigio de la marca sino la escala de la infraestructura. Desde 2014, eDreams ODIGEO opera como una plataforma de inteligencia artificial en su núcleo: más de 100 millones de búsquedas procesadas al día, más de 6.000 millones de predicciones automatizadas, y una capacidad de ingesta superior a 100 terabytes de datos cada 24 horas. Para un ingeniero de machine learning, es un entorno difícil de igualar.
La empresa ha apostado por consolidar esa ventaja. La inversión en formación casi se duplicó en un año, alcanzando las 99.335 horas anuales, con foco en competencias de IA. El 88% de la plantilla tiene menos de 40 años. La IA agéntica —sistemas capaces de generar código de forma autónoma bajo supervisión humana— ha incrementado la productividad de los equipos de ingeniería un 47% en el último ejercicio.
La retención cuenta tanto como el reclutamiento. La rotación voluntaria cayó un 14% en el ejercicio fiscal 2026 y la antigüedad media creció un 6%. Lindsay Auty, Chief People Officer de la compañía, lo resumió con claridad: eDreams ODIGEO ya no compite por talento del sector viajes. Compite, a escala global, por los mejores ingenieros del mundo.
La pregunta que queda abierta es si una plataforma de suscripción de viajes puede sostener la velocidad de innovación que justifica ocupar ese espacio junto a Apple o Netflix. De momento, los números sugieren que el mercado cree que sí.
eDreams ODIGEO, the world's largest travel subscription company, has crossed into rarefied air. Out of nearly 29,000 candidates who applied for jobs last year, the company hired 400 people. That works out to a 1.4% acceptance rate—a figure that places the Madrid-based travel tech firm alongside Netflix, Apple, and Microsoft in what the industry calls the "1% Club," a loose confederation of the world's most selective technology employers.
The numbers grow even more austere when you account for the full pipeline. More than 40,000 applications came in across all roles. When you divide 400 hires by that total, the acceptance rate drops to 0.98%—lower than Harvard's 4.2% admission rate for its most recent entering class. It is a striking comparison, and it reveals something about how technology talent markets have evolved. A travel company is now competing for engineers the way Ivy League universities compete for students.
What draws people to eDreams ODIGEO is not the prestige of the brand—though the company has been around since the early days of online travel booking. It is the infrastructure. Since 2014, the company has operated as an AI-first platform, meaning artificial intelligence is not bolted onto the business; it is the business. The system processes more than 100 million searches daily and generates over 6 billion automated predictions each day. Engineers working there have access to an architecture that can ingest more than 100 terabytes of data every 24 hours. For someone building machine learning systems, this is a playground.
The company has doubled down on this advantage. Training investment nearly doubled year-over-year, reaching 99,335 hours annually, up from 48,933 the year before. The focus is on AI competencies. The workforce skews young—88% are millennials or younger—which means the company is building for the next decade, not managing the last one. The engineering teams are concentrated in European hubs: Barcelona, Madrid, Porto, and Milan. From these centers, they develop the personalization models and core technologies that power Prime, eDreams ODIGEO's subscription platform, which is aiming to reach 13 million members by March 2030.
There is a productivity story embedded here too. Agentic AI—systems that can generate code autonomously under human oversight—has boosted engineering productivity by 47% in the past year. The most advanced teams now have AI writing all new code, though humans remain in control of design and direction. This is not science fiction; it is happening in real time at a travel company in Spain.
Retention matters as much as recruitment. Voluntary turnover fell 14% in the 2026 fiscal year, a significant achievement in a sector notorious for talent churn. Average tenure increased by 6%. The company has earned spots on LinkedIn's list of Spain's best places to work in 2025 and 2026, and has appeared on Forbes' rankings from 2022 through 2026. Lindsay Auty, the company's Chief People Officer, framed the hiring selectivity as a sign of transformation: eDreams ODIGEO is no longer just a travel company competing for travel talent. It is a technology company competing globally for the best engineers, period.
What happens next will test whether this talent concentration actually delivers. The company has set an ambitious roadmap to 2030. It has the people. It has the infrastructure. It has the capital to invest in training. The question is whether a travel subscription service, however well-engineered, can sustain the kind of innovation velocity that justifies sitting in the same talent market as Apple and Netflix. For now, the numbers suggest the market believes it can.
Citas Notables
We are no longer competing solely within the travel sector, but with the world's leading technology corporations for the best talent. By bringing professionals of this caliber into our AI-driven ecosystem, we ensure our teams have the capacity and excellence needed to execute our roadmap toward 2030.— Lindsay Auty, Chief People Officer, eDreams ODIGEO
La Conversación del Hearth Otra perspectiva de la historia
Why does a travel company need to compete with Apple and Microsoft for engineering talent? What's the actual technical challenge?
They're not really a travel company anymore—they're an AI infrastructure company that happens to sell travel subscriptions. Processing 100 million searches a day and generating 6 billion predictions daily requires the same kind of systems thinking you'd need at a search engine or a cloud provider. The talent they're hiring isn't writing booking flows; they're building machine learning systems at scale.
The 1.4% acceptance rate—is that real selectivity, or is it marketing?
It's real in the sense that they're genuinely turning away 98% of applicants. But it's also a function of how they're recruiting. When you're known as an AI-first company with cutting-edge infrastructure, you attract a lot of applications from people who aren't actually qualified. The real signal is that they're competing with Harvard on acceptance rates, which suggests they're being genuinely rigorous about who gets through.
The 47% productivity boost from agentic AI—that seems almost too good to be true.
It's plausible if you're measuring the right thing. If AI is writing boilerplate code and handling routine tasks, engineers can spend more time on architecture and novel problems. That's a real productivity gain. But it also means the company is betting heavily that this technology stays stable and that human oversight actually works. If it doesn't, they've built their entire hiring strategy on a foundation that could shift.
Why does the company care so much about training hours and demographic profile?
Because they're trying to build institutional memory and culture at a company growing very fast. If 88% of your workforce is under 40, you need to actively teach people how the company works, what the standards are, what the history is. Training isn't just about AI skills—it's about cohesion. And the 14% drop in voluntary turnover suggests it's working.
What's the real risk here?
Execution. They have the talent and the infrastructure, but they're trying to grow Prime to 13 million subscribers by 2030 in a market where travel subscriptions are still unproven at scale. All the engineering talent in the world doesn't guarantee product-market fit. And if the AI productivity gains don't materialize the way they're projecting, the whole talent strategy becomes harder to justify.