Position overviewPosted 1 month ago
Staff / Lead Data Engineer
Agoda →Full-time8+ years
Bangkok, Thailand
Compensation
THB 150,000 - THB 250,000
THB / month
Estimated range. Confirm compensation with the employer.
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Listing record updated: September 5, 2026. We archive records after 60 days without an update. This date does not confirm that the employer is still hiring.
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About the position
You will join Agoda's Display & App Marketing engineering team to build and maintain large-scale systems that power performance marketing across global advertising channels. Your work will involve managing high-volume hotel feeds, processing advertisement images, and integrating with major advertising platforms like Google Ads and Meta. You will collaborate closely with Marketing, Product, and Data teams to deliver reliable, efficient, and scalable engineering solutions that drive real business impact. This role offers the opportunity to shape systems and working methods end-to-end, from design and implementation to operational excellence at a global scale.
You will design, build, and operate backend services and data pipelines that support performance marketing use cases, including hotel feeds, ad platform integrations, and experiment data. You will actively participate in the full development lifecycle, from design and implementation to testing, deployment, and production support. You will proactively identify and improve system reliability, scalability, data quality, and operational efficiency while writing clear, maintainable code and engaging in code reviews and technical discussions.
Responsibilities
- Design, build, and operate backend services and data pipelines for performance marketing
- Contribute to technical design discussions and drive implementation of production systems
- Participate in the full development lifecycle including design, implementation, testing, deployment, and support
- Proactively identify and improve system reliability, scalability, data quality, and operational efficiency
- Write clear, maintainable code and actively participate in code reviews and technical discussions
- Collaborate with Product, Marketing, and other Engineering teams to deliver effective solutions
- Support and improve team engineering standards including CI/CD, monitoring, and documentation
- Make technical trade-offs across performance, quality, and cost
- Participate in hiring, onboarding, and knowledge sharing
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field
- 8+ years of experience focused on backend and/or data engineering
- Strong proficiency in Scala (preferred) or another JVM language (e.g., Java, Kotlin)
- Strong proficiency in SQL
- Experience building and operating data processing and pipeline systems (e.g., Spark, Kafka, workflow orchestration tools)
- Experience with messaging and asynchronous systems (e.g., RabbitMQ, Kafka)
- Demonstrated track record of driving architectural decisions and improving team-level engineering metrics and system reliability
- Ability to lead incident response: identify root cause, drive resolution, and communicate clearly
- Experience working in Agile, cross-functional teams
- Strong English communication skills, written and verbal
- An engineering-driven mindset with strong analytical, problem-solving, and systems-thinking abilities
- Experience mentoring and coaching engineers
Nice to have
- Deep experience with Spark-based distributed data pipelines, including performance tuning and query plan optimization
- Experience integrating with external APIs or third-party platforms at scale (e.g., Google Ads, Meta), with familiarity in advertising, marketing, or experimentation systems
- Experience identifying, monitoring, and addressing data quality risks in production, supported by observability and monitoring tooling (e.g., Grafana, Prometheus)
- Experience with CI/CD pipelines and modern DevOps practices
- A track record of cross-team technical influence — creating reusable patterns or frameworks, and shaping engineering standards beyond your immediate team
Hiring Process
1. Application Review
2. Technical Screening
3. Onsite Interviews
4. Final Interview
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