Company Description:
AIRR Labs, headquartered in Singapore, is a leading e-commerce enabler in Southeast Asia, specializing in FMCG, Beauty, and Lifestyle brands on platforms like TikTok Shop, Shopee, and Lazada. Established in 2019, AIRR Labs has over 350 experts across Thailand, the Philippines, Vietnam, Malaysia, and Singapore, with a technology hub in Vietnam. The company provides comprehensive digital commerce solutions, including content strategy, performance marketing, store management, short-form video production, livestreaming, and multi-channel fulfillment. As a certified TikTok Strategic Agency, Shopee Premium Enabler, and Lazada Star Enabler, AIRR Labs partners with global brands such as Unilever, Colgate-Palmolive, Estée Lauder, and Adidas.
The Role:
- 40% Data Architecture — Partner with product and software engineering teams to design scalable data models, define architecture standards, and ensure clean data flows from source to consumption.
- 50% Data Engineering — Build and optimize ETL/ELT pipelines, write performant SQL and transformation logic, and maintain data quality across TB-scale datasets.
- 10% Infrastructure Reliability — Monitor platform uptime, troubleshoot incidents, and keep our cloud data infrastructure healthy.
What You’ll Do:
- Partner with software engineers and product teams to design data modelling, schema design, and platform architecture.
- Design and maintain scalable data pipelines across our AWS (S3, Lambda) and SingleStore environment.
- Write efficient, optimized SQL for analytics, reporting, and data product use cases.
- Define architecture standards, naming conventions, and documentation practices for the data layer.
- Help shape a coherent, well-structured data layer that can serve as the foundation for future AI and ML initiatives.
- Monitor infrastructure health, respond to incidents, and drive root-cause analysis.
What We’re Looking For:
- 6+ years of experience in Data Engineering, Data Platform Engineering, or related fields.
- Strong experience building scalable data systems and pipelines from scratch.
- Strong SQL skills and understanding of data modeling, partitioning, and performance optimization.
- Hands-on experience with AWS services such as S3 and Lambda.
- Experience with analytical databases such as SingleStore, Snowflake, BigQuery, ClickHouse, Redshift, or similar.
- Experience with orchestration tools such as Airflow, dbt, or similar technologies.
- Proficiency in Python or another scripting/programming language.
- Strong problem-solving skills with the ability to think in systems and engineering trade-offs.
- High ownership, independent working style, and curiosity toward emerging technologies and AI-enabled workflows.