Senior / Staff Data Engineer (BI) – Customer Experience Group

About Agoda

Agoda is a global leader in travel, founded in 2005 by two entrepreneurial friends passionate about making world exploration accessible to all. Now part of Booking Holdings (NASDAQ: BKNG), Agoda's diverse workforce spans over 7,000 employees from 90 countries. Through millions of hotels, holiday rentals, flights, and experiences, Agoda connects travelers with destinations worldwide every day.

Within Agoda, the Data department plays a vital role, managing all company data requirements by delivering operational and analytical databases, queue systems, business intelligence tools, and data science technologies. The team’s mission is to scale and innovate data usage company-wide while maintaining a culture of diversity and experimentation. Data engineering supports business users, product managers, engineers, and more, enabling better decision-making and enhanced customer experiences.

Role Overview

As a Senior/Staff Data Engineer in the Customer Experience Group (CEG), you will architect, implement, and sustain the data and software infrastructure that supports how CEG serves customers and agents across multiple contact channels. You will collaborate intensively with Product, Operations, Analytics, Workforce Management, DevOps, and engineering teams to deliver dependable data pipelines, scalable models, internal tooling, and insightful analytics to boost customer satisfaction and operational performance.

You will fluidly alternate between engineering disciplines—creating pipelines, data models, internal services, tooling, and optimizations—and analytics tasks, including answering business questions, developing dashboards, and conducting thorough analyses. At the Staff level, your influence will extend to strategic data tooling direction, cross-team architectural leadership, and raising engineering standards for the CEG data ecosystem.

Key Responsibilities

• Develop and maintain scalable ETL/ELT pipelines ingesting and transforming data from CEG’s internal systems (case management, telephony, chat, bots, QA tools, workforce management, CRM) plus third-party tools and logs.
• Model and optimize data warehouse tables, marts, and views powering CEG reporting, monitoring, forecasting, quality assurance, and experiments.
• Uphold data quality by implementing validation checks, anomaly detection, and comprehensive monitoring of critical datasets and metrics.
• Collaborate with stakeholders to define and enforce data definitions, establish SLAs, and clarify ownership over vital tables and metrics.
• Optimize performance and cost-effectiveness of data jobs through techniques like partitioning, indexing, query tuning, and storage format selection, tailored for high-volume CEG data.
• Contribute to standardizing tooling and best practices in collaboration with data platform and engineering teams, including version control, CI/CD pipelines, code review, documentation, and runbook creation.
• Design, build, and refine internal data tools and products, such as self-service analytics platforms, case monitoring dashboards, alerting systems, investigator and QA tools, and agent performance views.
• Use programming languages like Python, Java, Golang, and JavaScript/TypeScript for implementing APIs, data services, and lightweight user interfaces that provide actionable data to agents, managers, and operations.
• Partner with product managers and operations teams to identify operational challenges and translate them into tangible data tool solutions, overseeing the full development lifecycle.
• Apply robust software engineering principles—including testing, code reviews, continuous integration/deployment, and observability—to ensure data products are stable, maintainable, and extensible.
• At the Staff level, lead strategic planning and roadmapping for essential data tools and platforms within CEG, promoting reuse across geographical regions, business units, and communication channels.
• Work closely with business and product teams to reframe their questions into analytical problems and design clear, actionable analytic solutions.
• Create and maintain dashboards and reports covering metrics such as contact volumes, handling time, quality scores, customer outcomes, agent performance, and alerts to empower data-driven decisions.
• Conduct in-depth analyses to detect patterns in contact trends, operational issues, and agent effectiveness; diagnose root causes and propose data-backed intervention recommendations.
• Define and manage KPIs including CSAT, NPS, SLA, average handling time, first contact resolution, and quality measurements, ensuring consistency across CEG tools and teams.
• Communicate analytical results and business implications clearly and concisely to non-technical audiences.
• Serve as a trusted partner for CEG stakeholders including operations leaders, product and workforce management, QA, training, policy, and regional managers.
• Collaborate with data engineers, analysts, and scientists to align on data standards, reusable components, and shared datasets to optimize CEG data infrastructure.
• Provide mentorship to junior and middle-level colleagues on best practices in data engineering, analytics, and software development.
• Drive continuous process improvements including code review standards, automated testing, documentation, operations manuals, knowledge sharing sessions, and incident retrospectives.
• At the Staff tier, influence architecture and collaboration practices across teams to ensure the scalability and robustness of CEG’s data ecosystem in line with business growth.

Required Qualifications

• Minimum 8 years professional experience in roles such as Data Engineer, Analytics Engineer, or Data Analyst within data-centric environments (Staff level or equivalent impact usually requires 10+ years).
• Advanced SQL proficiency encompassing complex joins, window functions, aggregations, and query performance tuning.
• Hands-on expertise with at least one prominent data warehousing or big data platform such as BigQuery, Snowflake, Redshift, Hive, Spark, Vertica, or StarRocks.
• Practical experience using ETL/ELT orchestration frameworks like Airflow, dbt, or proprietary internal tools.
• Competency in one or more programming languages for data pipelines and services, including Python, Java, Golang, Kotlin, or JavaScript/TypeScript.
• Track record of delivering reliable, production-grade data pipelines and services with proper monitoring and maintainability considerations.
• Experience with business intelligence and visualization software such as Tableau, Power BI, Superset, Metabase, or Looker.
• Strong analytical mindset capable of translating business queries into data investigations and deriving transparent insights.
• Excellent communication skills to convey complex technical topics effectively to non-technical stakeholders.

Preferred Qualifications

• Familiarity with event-driven data, including logs, clickstreams, customer journeys, contact flows, and tracking information.
• Knowledge of data modeling methodologies such as dimensional modeling, Kimball approaches, data vault, star and snowflake schemas.
• Experience with A/B testing frameworks, experimentation platforms, and causal inference techniques.
• Understanding of machine learning pipelines and collaboration with data science teams on models related to routing, QA scoring, forecasting, or recommendations.
• Background in online consumer-facing products, travel industry, e-commerce, or marketplace environments.
• Proficiency in frontend or backend engineering for internal tooling, especially frameworks like React, Next.js, Node.js, or equivalents used by operational staff.
• Previous leadership roles at Staff or Tech-Lead level, including guiding the technical direction and mentoring multiple engineers and analysts.

Additional Information

This is an equal opportunity position welcoming candidates from diverse backgrounds, committed to merit-based employment without discrimination. Agoda maintains confidentiality of applicant data and reserves rights regarding unsolicited agency submissions.