Staff / Lead Data Engineer, Data Warehouse Architecture

Traveloka; Singapore; On-site; SGD 140,000 - 200,000; Full time

Job summary

Traveloka is seeking a Staff/Lead Data Engineer to own the architecture and evolution of its enterprise data warehouse in Singapore. You will define data models, governance, and consumption across the organisation to enable analytics, reporting, and downstream data products.

This hands-on leadership role requires experience designing scalable data warehouse architectures and mentoring engineers to raise the team's standards. OTA and travel tech domain experience is highly valued.

Qualifications

• Minimum 10+ years Data Engineering experience.
• Proven experience designing large-scale data warehouses from ground up.
• Strong knowledge of dimensional modelling, Data Vault, conformed models, and modern data architecture.
• Experience with OTA, travel tech, e-commerce, marketplace, fintech is highly preferred.

Responsibilities

• Own the end-to-end data warehouse architecture, including raw, staging, core/conformed, and data mart layers.
• Design scalable models for complex transactional domains such as bookings, payments, cancellations/refunds, amendments, supplier/customer flow data.
• Establish a single, governed metrics and definition layer to ensure consistency across business units and downstream consumers.
• Define and enforce data modelling, data contracts, quality, and engineering standards.
• Partner with Analytics, Data Science, Product, Finance, and business teams to translate requirements into scalable data solutions.
• Lead technical and design reviews and act as a trusted advisor for complex data architecture decisions.
• Mentor Data Engineers and raise the overall engineering and modelling standards of the team.

Skills

Data engineering

Data warehouse architecture

Dimensional modelling

Data Vault

SQL

Leadership

Mentoring

BigQuery

dbt

Tools

BigQuery

dbt

ETL tooling

Job description

Job De ion

Job ID: MJ000352

We are looking for a Staff / Lead Data Engineer to own the architecture and evolution of our enterprise data warehouse. You will define how data is modelled, governed, and consumed across the organisation, creating a scalable foundation for analytics, reporting, and downstream data products.

This is a hands-on technical leadership role for someone who has personally designed and scaled complex data warehouse architectures, rather than only building pipelines within an existing framework.

Key Responsibilities

• Own the end-to-end data warehouse architecture, including raw, staging, core/conformed, and data mart layers.
• Design scalable models for complex transactional domains such as bookings, payments, cancellations/refunds, amendments, supplier/customer flow data.
• Establish a single, governed metrics and definition layer to ensure consistency across business units and downstream consumers.
• Define and enforce data modelling, data contracts, quality, and engineering standards.
• Partner with Analytics, Data Science, Product, Finance, and business teams to translate requirements into scalable data solutions.
• Lead technical and design reviews and act as a trusted advisor for complex data architecture decisions.
• Mentor Data Engineers and raise the overall engineering and modelling standards of the team.

Requirements

• Minimum 10+ years of Data Engineering experience, with experience operating at Staff, Lead, Principal, or equivalent level preferred.
• Proven experience designing large-scale data warehouses from the ground up.
• Strong knowledge of dimensional modelling, Data Vault, conformed models, and modern data architecture principles.
• Advanced SQL skills and hands-on experience with BigQuery, dbt, or equivalent technologies.
• Experience designing semantic/metrics layers and data contracts across multiple consumers.
• Strong understanding of large-scale transactional data and complex business logic.
• Strong technical leadership with experience reviewing architecture and mentoring other engineers.
• Experience in OTA, travel tech, e-commerce, marketplace, fintech is highly preferred.