Senior Data Platform Engineer

About AIRR Labs:

Founded in 2019 and headquartered in Singapore, AIRR Labs is a leading e-commerce enabler in Southeast Asia for FMCG, Beauty and Lifestyle brands. We have 350+ people across Thailand, the Philippines, Vietnam, Malaysia and Singapore, with our technology hub in Vietnam. We are a certified TikTok Strategic Agency, Shopee Premium Enabler and Lazada Star Enabler, and we partner with brands such as Unilever, Colgate-Palmolive, Estée Lauder and Adidas.

About the Role:

We are turning AIRR's data into a platform. Today, data from TikTok Shop, Shopee, Lazada, livestream, media and fulfilment sits across tools and teams. The Centralized Data Platform (CDP) unifies it into one trusted layer. Every team and client consumes it as a service through APIs and MCP, never through ad-hoc exports.

You will be the senior engineer who builds that platform. You will set the standards, ship the core pipelines and launch the serving layer that our commerce, media and AI products run on.

Share of work:

• Data architecture (35%): Unified data model across marketplaces, brands and markets; architecture standards; data contracts with source teams.
• Data engineering (35%): ELT pipelines, marketplace API ingestion, transformation logic, data quality on TB-scale datasets.
• Data serving (20%): API and MCP layer so internal teams, clients and AI agents consume data as a service.
• Platform reliability (10%): Uptime, observability, incident response, cost control.

What You’ll Do:

• Architect the CDP: Design the core data model (orders, products, creators, campaigns, livestreams, inventory) across TikTok Shop, Shopee, Lazada and five markets.
• Set the standards: Define naming conventions, layering (raw → clean → serving), documentation and data contracts that source teams sign up to.
• Build the pipelines: Ingest marketplace and internal APIs at scale on AWS (S3, Lambda) and SingleStore, handling rate limits, schema changes and late-arriving data.
• Serve data as a product: Build and own the API and MCP layer, with clear SLAs, versioning and access control, so consumers never query raw tables.
• Guarantee trust: Put automated data quality checks, lineage and observability in place; drive root-cause analysis on incidents.
• Enable AI: Shape a semantic layer that AI agents and ML use cases can query safely through MCP.
• Partner across teams: Work with product, software engineering, commercial and client teams to turn their data needs into platform capabilities.

What we're looking for:

Must-haves:

• 6+ years in data engineering or data platform engineering, including at least one platform built from scratch.
• Expert SQL and data modelling (dimensional, partitioning, performance tuning).
• Hands-on AWS (S3, Lambda) and an analytical database (SingleStore, Snowflake, BigQuery, ClickHouse, Redshift or similar).
• Orchestration (Airflow, Dagster or similar) and transformation tooling (dbt or similar).
• Strong Python, including building data APIs (FastAPI, REST or GraphQL).
• Data quality and observability practice: testing, monitoring, lineage.
• Platform mindset: treats internal teams as customers, writes clear contracts and docs.
• High ownership and comfort making architecture trade-offs independently.
• Working English for regional collaboration.

Nice-to-haves:

• Experience with MCP, LLM tooling or semantic layers for AI agents.
• Experience with e-commerce marketplace APIs (TikTok Shop, Shopee, Lazada) CDC or streaming (Kafka, Kinesis, Debezium).
• Infrastructure as code (Terraform, CloudFormation).
• Data governance and access control across multiple clients or brands.