Data Solutions Architect / Lead Data Engineer

About AIRR Labs:
AIRR Labs, headquartered in Singapore, is a leading e-commerce enabler in Southeast Asia, specializing in FMCG, Beauty, and Lifestyle brands across platforms such as TikTok Shop, Shopee, and Lazada. Since 2019, AIRR Labs has grown to more than 350 experts across Thailand, the Philippines, Vietnam, Malaysia, and Singapore, with a technology hub in Vietnam.
We partner with global brands including Unilever, Colgate-Palmolive, Estée Lauder, and Adidas to deliver end-to-end digital commerce solutions spanning content strategy, performance marketing, livestreaming, store operations, and fulfillment.
About the Role:
This is a senior technical leadership role with direct ownership of the data foundation that supports the business. The successful candidate will set the architectural direction for the data platform and remain hands-on across code, pipelines, and systems.
This is a high-impact opportunity to lead strategic projects, collaborate directly with senior leadership, and shape the data backbone of a core ecommerce and SaaS business.
Role Overview:
Architecture (50%) - Define data models, schema design, and platform architecture; set the technical direction and standards that the wider organization adopts and builds upon.
Engineering (35%) - Design, build, and optimize ETL/ELT pipelines, author performant SQL and transformation logic, and maintain data quality across TB-scale datasets. This role remains hands-on in production.
Operations (15%) - Monitor platform health, resolve incidents, and ensure the reliability and performance of the cloud data infrastructure.
Key Responsibilities:
Architecture:
Own data modelling, schema design, and end-to-end platform architecture.
Establish architecture standards, naming conventions, and documentation practices across the data layer.
Pipelines:
Design, build, and maintain scalable data pipelines across our AWS (S3, Lambda) and data warehouse environment.
Write efficient, optimized SQL for analytics, reporting, and data product use cases.
AI Foundation:
Build the data layer that serves as the foundation for the organization's AI and machine learning roadmap.
Reliability:
Monitor infrastructure health, respond to incidents, and drive root-cause analysis.
Your skills and experience
Requirements:
8+ years in data or software engineering, including a track record of owning a data platform or major system end-to-end.
Demonstrated ownership of architecture decisions - build-versus-buy calls, technology selection, and setting technical direction across multiple teams.
Strong SQL skills with experience optimizing complex queries on large datasets (TB-scale).
Hands-on experience with AWS S3 and Lambda. Experience with Databricks or a comparable analytical database (e.g., ClickHouse, Single Store, BigQuery).
Solid understanding of data modelling (star schema, ERD, normalization trade-offs).
Familiarity with ETL/ELT orchestration tools (e.g., Airflow, dbt, Apache Dolphin).
Proficiency in Python or another scripting language for pipeline development.
Prior experience in ecommerce or tech industry preferred.
What We Offer:
Opportunity to work on cutting-edge AI technologies that transform how businesses create content.
A collaborative, innovative environment with opportunities for professional growth.