Staff Data Engineer – Display Marketing Team
Pubblicato il 23-08-2026 - Agoda in Treviso
About Agoda
At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
Today, we are part of Booking Holdings (NASDAQ: BKNG), with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you’re ready to begin your best journey and help build travel for the world, join us.
Get to Know Our Team
This role is part of Agoda’s Display & App Marketing engineering team, focused on building and improving large-scale systems that power paid marketing across global advertising channels, including Display Ads and App Install campaigns.
Our systems handle high-volume hotel feeds (price,
availability, content), image processing for advertisements, advertising platform integrations (Google Ads, Meta, etc.), and data pipelines that support experimentation and optimization.
You will work closely with Marketing, Product, and Data teams to deliver reliable, efficient, and scalable engineering solutions, with strong exposure to marketing strategy, experimentation, and real business impact. The team is growing and evolving, giving you the opportunity to shape systems and ways of working end-to-end—from design and implementation to operational excellence at global scale.
In this Role, you will get to
- Design, build, and operate backend services and data pipelines that support performance marketing use cases, including hotel feeds, ad platform integrations, and experiment data
- Contribute to technical design discussions and drive implementation of production systems running at scale
- Tak