
Senior/Staff Data Platform Engineer - (Bangkok based, relocation provided)
Agoda
Senior/Staff Data Platform Engineer - (Bangkok based, relocation provided)
Senior/Staff Data Platform Engineer role at Agoda, based in Bangkok with relocation provided. Responsibilities include designing, building, and operating a cloud-native data platform using Snowflake and public cloud infrastructure. Requires hands-on experience with public cloud platforms, Snowflake administration, dbt, Infrastructure-as-Code, and pipeline orchestration.
Senior/Staff Data Platform Engineer - (Bangkok based, relocation provided)
Senior/Staff Data Platform Engineer role at Agoda, based in Bangkok with relocation provided. Responsibilities include designing, building, and operating a cloud-native data platform using Snowflake and public cloud infrastructure. Requires hands-on experience with public cloud platforms, Snowflake administration, dbt, Infrastructure-as-Code, and pipeline orchestration.
Salary
Core Qualifications
Technical (Must-have)
Tools (Must-have)
Key Responsibilities
- Provision and manage cloud environments including storage, networking, and IAM across public cloud platforms (AWS / GCP / Azure).
- Architect and administer Snowflake as the organization's unified Data Lake and Data Warehouse platform.
- Define and enforce Data Access Policies with encryption, IAM, and Snowflake network policies.
- Build and maintain dbt transformation models with Git-based version control across staging and production data layers.
- Define platform standards, and best practices for data ingestion, transformation, and consumption layers.
- Responsible for the end-to-end design, provisioning, and operation of the cloud data platform — spanning raw ingestion zones through to curated, analytics-ready data layers — ensuring reliability, scalability, and cost efficiency across all environments.
- Maintains overall responsibility for the unified data warehouse and lake platform architecture, including performance tuning, resource management, cost governance, and the evolution of the platform as organizational data needs grow.
- Owns the transformation layer from design through to production, ensuring data models, testing frameworks, and documentation are accurate, consistent, and fit for consumption across all downstream use cases.
- Drives the definition and adoption of platform-wide standards covering data ingestion, transformation, and consumption patterns, and evaluates tooling and architectural decisions as the platform matures.