Staff Data Engineer
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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.
Sponsor
Agoda
Title
Staff Data Engineer
Description
About the team: The Data department at Agoda enables data-driven decision making across the company by building operational and analytical databases, queue systems, BI tools, and data science infrastructure. The Data Core Apps team operates large-scale systems spanning multiple data centers, handling millions of writes per second and tens of petabytes of data. We focus on real-time ingestion, replication, enrichment, storage and analytics — pushing big-data technologies to the edge.
Employment type
Full-time
Location
Level 22, 8 Chifley Square, Sydney NSW, 2000
Key responsibilities
- Design and develop software services and platform components (including APIs and backend services) supporting data and metadata workflows.
- Own end-to-end delivery of medium-to-large initiatives across teams, including design, implementation, testing, rollout, and operational readiness.
- Build and maintain data/metadata integrations and pipelines (e.g., ingestion, connector development, scheduling, monitoring and failure handling).
- Drive system design and architecture decisions, document trade-offs, and participate in cross-team design/architecture reviews.
- Ensure operational excellence: observability (logging/metrics/tracing), alerting, incident response support, root-cause analysis, and prevention actions.
- Improve reliability and scalability through performance tuning, capacity planning, and high-availability patterns.
- Establish engineering standards for code quality, testing strategies, and release safety; perform high-quality code reviews.
- Mentor engineers and enable other team members through knowledge transfer, documentation, and pairing.
Required skills, qualifications and experience
- 7+ years of experience in software and data engineering.
- Expert-level Apache Spark knowledge (design, tuning, debugging).
- Expert-level JVM understanding and proficiency in Java or Scala.
- Strong SQL skills.
- Familiarity with Python for tooling and scripting.
- Experience with Linux systems administration.
- Experience debugging and reasoning about production issues in distributed systems.
- Good understanding of data architecture principles.
- Experience with Big Data ecosystems and tools (Hadoop, S3, Kafka, etc.).
- Analytical problem-solving capabilities.
Desirable (nice-to-have)
- Experience working in Data Infrastructure or Data Platform teams.
- Contributions or experience with open-source products.
- Experience with Kubeflow, data lineage, data quality systems, or ETL tooling.
- Previous work at scale (multi-datacenter, multi-PB environments).
Open dates
- Posting date: 2026-03-17
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