Staff Data Engineer - Display Marketing Team (Bangkok based, relocation provided)

About the role

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 1. Design, build, and operate backend services and data pipelines that support performance marketing use cases, including hotel feeds, ad platform integrations, and experiment data 2. Contribute to technical design discussions and drive implementation of production systems running at scale 3. Take part in the full development lifecycle: design, implementation, testing, deployment, and production support 4. Proactively identify and improve system reliability, scalability, data quality, and operational efficiency 5 Write clear, maintainable code and actively participate in code reviews and technical discussions 6. Collaborate with Product, Marketing, and other Engineering teams to clarify requirements and deliver effective solutions 7. Support and improve the team's engineering standards, including CI/CD, monitoring, and documentation 8. Make technical trade-offs across performance, quality, and cost 9. Participate in hiring, onboarding, and knowledge sharing, in line with your experience and interests What You'll need to Succeed 1. Bachelor's degree in computer science, Engineering, or a related field (or equivalent practical experience)8+ years of experience, with a focus on backend and/or data engineering 2. Strong proficiency in Scala (preferred) or another JVM language (e.g. Java, Kotlin) 3. Strong proficiency in SQL 4. Experience building and operating data processing and pipeline systems, e.g. Spark, Kafka, workflow orchestration tools 5. Experience with messaging and asynchronous systems (e.g. RabbitMQ, Kafka) 6. Demonstrated track record of driving architectural decisions and improving team-level engineering metrics and system reliability 7. Ability to lead incident response: identify root cause, drive resolution, and communicate clearly 8. Experience working in Agile, cross-functional teams 9. Strong English communication skills, written and verbal 10. An engineering-driven mindset with strong analytical, problem-solving, and systems-thinking abilities 11. Experience mentoring and coaching engineers, with a genuine interest in helping others grow It's great if you have 1. Deep experience with Spark-based distributed data pipelines, including performance tuning and query plan optimization 2. Experience integrating with external APIs or third-party platforms at scale (e.g. Google Ads, Meta), with familiarity in advertising, marketing, or experimentation systems 3. Experience identifying, monitoring, and addressing data quality risks in production, supported by observability and monitoring tooling (e.g. Grafana, Prometheus) 4. Experience with CI/CD pipelines and modern DevOps practices 5. A track record of cross-team technical influence - creating reusable patterns or frameworks, and shaping engineering standards beyond your immediate team #telaviv #jerusalem #LI-SK1 #IT #ENG #4 #LI-PS4 #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #philadelphia #dallas #houston #austin #seattle #sydney #melbourne #perth #toronto #vancouver #montreal #shanghai #beijing #shenzhen #prague #Brno #Ostrava #cairo #alexandria #giza #estonia #paris #berlin #munich #hamburg #stuttgart #cologne #frankfurt #hongkong #budapest #jakarta #bali #dublin #telaviv

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