Lead Data Engineer: Enterprise Data Warehouse Architect

Traveloka; Singapore; On-site; SGD 180,000 - 230,000; Full time

Job summary

Traveloka is seeking a Staff/Lead Data Engineer in Singapore to own the enterprise data warehouse architecture and its evolution. You will define data models, governance, and consumption across the organization, creating a scalable analytics foundation.

This hands-on technical leadership role requires experience designing and scaling large data warehouse architectures and mentoring engineers to elevate standards across the team.

Qualifications

• 10+ years of Data Engineering experience and leadership track record.
• Experience designing large-scale data warehouses from the ground up.
• Strong knowledge of dimensional modelling, Data Vault, conformed models, and modern data architectures.
• Advanced SQL skills and hands-on use of BigQuery, dbt, or equivalent.
• Experience designing semantic/metrics layers and data contracts.

Responsibilities

• Own the end-to-end data warehouse architecture (raw, staging, core/conformed, data marts).
• Design scalable models for bookings, payments, cancellations/refunds, and related data flows.
• Establish a governed metrics and definition layer for consistency.
• Define and enforce data modelling, contracts, quality, and standards.
• Partner with Analytics, Data Science, Product, Finance to translate requirements into scalable solutions.
• Lead technical reviews and mentor engineers on architecture decisions.
• Mentor Data Engineers to raise engineering and modelling standards.

Skills

BigQuery

dbt

SQL

Data Warehouse design

Data modelling

Leadership

Mentoring

Travel tech domain

Tools

BigQuery

dbt

Job description

Traveloka is seeking a Staff/Lead Data Engineer in Singapore to own the enterprise data warehouse architecture and its evolution. You will define data models, governance, and consumption across the organization, creating a scalable analytics foundation.

This hands-on technical leadership role requires experience designing and scaling large data warehouse architectures and mentoring engineers to elevate standards across the team.