Agoda
[BI] Senior BI Developer (Analytics Engineer)
Bangkok, Thailand
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- Role family
- Data & ML
- Seniority
- Senior
- Country
- TH
- Work mode
- Remote-friendly
- First seen by hirly
- 10 Sept 2026
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the posting
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.
THE OPPORTUNITY
- As a Senior BI Developer, you will be a key individual contributor building trusted data
- products for Agoda’s technology organization, including curated datasets, metrics,
- dashboards and visualizations, and scalable data transformations. You will work closely
- with engineers, engineering managers, team leads, and senior leadership to help the
- organization make better decisions with data. This role combines analytics, metrics
- definition, and stakeholder consulting with hands-on data engineering and development
- IN THIS ROLE, YOU’LL GET TO
- Act as a partner and consultant to engineering managers and leaders: translate
- stakeholder and engineering questions into measurable metrics/information such
- as developer velocity, cost efficiency, and code quality, and keep those definitions
- consistent across reports.
- Design, build, and maintain ETL/ELT transformations, including Spark/Python
- workflows and warehouse models, so data is accurate, timely, tested, and fit for
- reporting. As a Senior, review others’ pipeline and metric work, raise delivery
- standards, and unblock the team.
- Analyze large datasets with SQL and Python to support engineering and operational
- decisions.
- Design and maintain dashboards and visual reports so engineering managers and
- leaders can explore metrics (for example developer velocity, cost efficiency, and
- code quality) without a ticket for every chart.
- Improve data reliability through validation, quality checks, observability, production
- troubleshooting, and query performance tuning. Own published metrics: explain
- filters and grain, flag numbers that should not be trusted, and recommend next
- steps.
- Use AI tools (for example Cursor, Claude, or similar) to accelerate SQL
- development, testing, refactoring, analysis, pipeline work, and documentation, and
- reject unsafe or unverified output before it reaches production or stakeholders.
- WHAT YOU’LL NEED TO SUCCEED
- 5+ years in business intelligence, analytics, and/or data engineering, with
- experience in both stakeholder consulting and hands-on pipeline or data-product
- work.
- Advanced SQL (joins, window functions, and performance on large datasets).
- Strong Python skills (or similar) for building data pipelines.
- Experience with ETL/ELT and orchestration (for example Kubeflow or similar).
- Strong analytical thinking: comfortable framing business questions, exploring data,
- and turning results into clear insights.
- Experience building dashboards or visual reports for stakeholders.
- Ability to switch context between stakeholder discussions and hands-on technical
- work — metrics definition/analysis one day, ETL or data modeling the next.
- Practical AI-assisted development: generate, review, test, and own the result. You
- can explain what you trusted AI to draft and what you verified yourself.
- Clear written and verbal English, and the ability to work independently with
- engineers and leaders in an agile environment.
- IT’S GREAT IF YOU HAVE
- Experience with software-delivery practices such as Agile/Scrum and CI/CD
- (GitHub Actions, GitLab CI, or similar).
- Interest in developer productivity or engineering analytics.
- Experience with common data platforms / big data technology (e.g., BigQuery,
- Snowflake, Redshift, Hive, Spark, Vertica, StarRocks, or similar).
- Hands-on experience with visualization or data-serving UIs such as Apache
- Superset, Tableau, or a lightweight web app.
- Experience building APIs or internal data products beyond dashboards, not only ad-
- hoc analysis.
- A degree in Computer Science, Engineering, Information Systems, or equivalent
- practical experience.
Please review our Hiring Process Guidelines before your interview — click here to learn how interviewing at Agoda works.
Discover more about working at Agoda
Agoda Careers https://careersatagoda.com
Facebook https://www.facebook.com/agodacareers/
LinkedIn https://www.linkedin.com/company/agoda
YouTube https://www.youtube.com/agodalife
Equal Opportunity Employer
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 .
Disclaimer
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.
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