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Agoda

[BI] Senior BI Developer (Analytics Engineer)

Bangkok, Thailand; Bangkok (One Bangkok Office)Thailand
Senior · Information Technology
POSTED 8 SEPTVERIFIED 31M AGO
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Open for
56d
since 8 Sept
Visa
UK
licensed sponsor
Hiring · 30d
308
−1 net · open roles
PythonSparkSnowflakeSQL

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).

Source · Agoda · GreenhouseFirst seen 2 NovOriginal ↗Method