Senior/Staff Data Engineer (BI Domain) - Bangkok based, relocation provided

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.

Join a small platform team building the next generation of natural-language analytics at Agoda. You will own the governed knowledge layer between our data warehouse and the applications, assistants, and analysts that consume it: metrics, domain context, quality signals, and the APIs that expose them. This is semantic modeling and knowledge engineering, not dashboard reporting or model training.

• You will design and operate the shared knowledge layer behind conversational analytics at Agoda: turning scattered business knowledge into versioned,
  reviewable assets that return consistent, current answers.
• You pair with a senior tech lead on product architecture. Your scope is the layer itself (models, context, validation, governance workflows) and how it is exposed through service and agent interfaces.

• →Model governed metrics, dimensions, joins, and grain for business domains
• →Structure expert context, glossaries, and validated question patterns as Git-reviewed assets
• →Build freshness, drift, and validation signals; treat stale knowledge as a production issue
• →Expose the layer through APIs so applications and agents get deterministic answers
• →Enable domain owners to propose, review, and publish knowledge without engineering deploys
• →Partner across analytics, product, and platform teams on access control and quality standards

• 4+ years in BI, analytics engineering, data platform, or software engineering with heavy data modeling
• Semantic or metrics-layer experience (LookML, dbt metrics, or equivalent)
• Strong SQL and analytical modeling on OLAP / warehouse systems
• Knowledge engineering: versioned definitions, peer review, contributor workflows
• API / service mindset: you design for multiple consumers, not a single dashboard
• Clear communication across engineering, analytics, and product partners

• Open-source semantic layer engines (Cube, MetricFlow patterns)
• Agent or tool-interface experience for LLM-powered applications
• NL-to-data products, retrieval, or evaluation harnesses
• Python or Node.js service development
• Large-scale e-commerce or travel analytics environments

 #Manila #Kualalumpur #Singapore #Bangkok #Thailand

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At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.

We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.

We do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.