Senior / Staff Data Engineer (BI) – CEG Team

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.

Get To Know Our Team

The Data department oversees all of Agoda’s data-related requirements. Our ultimate goal is to enable and increase the use of data in the company through creative approaches and the implementation of powerful resources such as operational and analytical databases, queue systems, BI tools, and data science technology. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company’s culture of diversity and experimentation. The role the Data team plays at Agoda is critical as business users, product managers, engineers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the Data department, but also the reward.

The Opportunity

As a  Senior/Staff Data Engineer in CEG (Customer Experience Group) , you will help design, build, and maintain the data and software foundations that power how CEG Business users serves customers and agents across all contact channels. You will work closely with Product, Operations, Analytics, Operations Efficiency, WFM, DevOps and engineering teams to deliver reliable data pipelines, scalable models, internal tools, and clear insights that improve customer experience and operational efficiency.

You are comfortable switching between  engineering work  (pipelines, data models, internal services, tooling, optimization) and  analytics work  (business questions, dashboards, deep‑dive analysis). You can talk to both engineers and business stakeholders in simple, clear language. At the  Staff level , you will also shape CEG’s data and tooling strategy, influence cross‑team architecture, and raise the overall engineering and data bar for the team.

What You’ll Do

Data Engineering

• Design, build, and maintain scalable  ETL/ELT pipelines  to ingest, transform, and serve data from CEG systems (case management, telephony, chat, bots, QA tools, WFM, CRM) and third‑party tools and logs.

• Develop and optimize  data models  (e.g., warehouse tables, marts, views) that power CEG reporting, monitoring, forecasting, QA, and experimentation.

• Ensure  data quality, reliability, and observability :

• Implement validation checks, anomaly detection, and monitoring for key CEG datasets and metrics.

• Work with stakeholders to define and enforce data definitions, SLAs, and ownership for critical tables and metrics.

• Improve  performance and cost efficiency  of data jobs and queries (e.g., partitioning, indexing, query tuning, storage format optimization) for high‑volume CEG data (calls, chats, emails, cases, events).

• Collaborate with data platform and engineering teams to  standardize tooling and best practices  (e.g., version control, CI/CD for data and services, code review, documentation, runbooks).

Data Tools & Product Development

• Design and build  data tools and internal products  for CEG (e.g., self‑service analytics, case monitoring dashboards, alerting systems, investigator tools, QA/review tools, agent performance views).

• Use languages such as  Python, Java, Golang, or JavaScript/TypeScript  to implement  APIs, data services, and lightweight UIs  that expose data in a usable way to agents, managers, and operations teams.

• Work closely with CEG product managers and operations to  translate operational pain points  into concrete data tools, from problem framing to delivery and iteration.

• Apply solid  software engineering practices —testing, code reviews, CI/CD, observability—to data products so they are reliable, maintainable, and easy to extend.

• At Staff level,  define and drive the roadmap  for key CEG data tools and platforms, ensuring reuse across regions, lines of business, and channels.

Data Analytics & Business Impact

• Partner with CEG product and business teams to  translate questions into data problems  and design clear analytic approaches.

• Build and maintain  dashboards and reports  (e.g., contact volumes, handling time, quality, customer outcomes, agent performance, spot alerts) that provide reliable metrics and self‑service access to data.

• Perform  deep‑dive analysis  to understand trends in contact patterns, customer issues, agent performance, and operational efficiency; identify root causes and propose practical, data‑driven recommendations.

• Define and maintain  metrics and KPIs  (e.g., CSAT, NPS, SLA, AHT, FCR, quality scores), ensuring consistent definitions across CEG teams and tools.

• Communicate findings in  simple, business‑friendly language , including clear implications and recommended next steps.

Stakeholder & Team Collaboration

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• Act as a  trusted data partner  for CEG stakeholders (operations leaders, product managers, WFM, QA, training, policy, and regional leadership).

• Work with other data engineers, analysts, and scientists to  align on data standards, reusable components, and shared datasets  for CEG.

• Mentor junior and mid‑level team members on  data engineering, analytics, and software engineering best practices .

• Contribute to  continuous improvement  of team workflows (code reviews, testing, documentation, runbooks, knowledge sharing, incident reviews).

• At Staff level, influence  cross‑team architecture and ways of working , making sure CEG’s data ecosystem scales with business growth.

Required Qualifications

• 8+ years working as a  Data Engineer, Analytics Engineer, or Data Analyst  in a data‑driven environment (Staff level typically 10+ or equivalent scope/impact).

• Strong  SQL  skills (complex joins, window functions, aggregation, query optimization).

• Experience with at least one major  data warehouse / big data technology  (e.g., BigQuery, Snowflake, Redshift, Hive, Spark, Vertica, StarRocks, or similar).

• Solid experience with  ETL/ELT tools or orchestration frameworks  (e.g., Airflow, dbt, internal frameworks).

• Proficiency in at least one  programming language for data and services  (e.g., Python, Java, Golang, Kotlin, or JavaScript/TypeScript).

• Experience building  production‑grade data pipelines and/or data services  with attention to quality, monitoring, and maintainability.

• Experience with  BI / visualization tools  (e.g., Tableau, Power BI, Superset, Metabase, Looker).

• Strong  analytical thinking : comfortable framing business questions, exploring data, and turning results into clear insights.

• Ability to communicate complex topics in  simple, concise language  to non‑technical stakeholders.

Preferred Qualifications

• Experience with  event‑driven data  (logs, clickstream, customer journey, contact flows, tracking data).

• Knowledge of  data modeling techniques  (e.g., dimensional modeling, Kimball, data vault, star/snowflake schema).

• Experience with  A/B testing, experimentation platforms, or causal analysis .

• Familiarity with  ML pipelines  or working with data science