Senior Data & Infrastructure Engineer
Vị trí này thuộc KIMEI Global, làm việc từ xa tại Việt Nam, hợp đồng toàn thời gian với trọng tâm 70% về kỹ thuật dữ liệu và 30% quản lý hạ tầng/DevOps. Ứng viên sẽ quản lý, tối ưu pipeline dữ liệu, tích hợp API (Amazon SP-API, Shopify), vận hành hệ thống (Airbyte, Dagster, Redshift), triển khai IaC với Terraform và tự động hóa CI/CD qua GitHub Actions/GitLab CI. Môi trường đa quốc gia, KPI rõ ràng, lộ trình phát triển rõ nét.
Yêu cầu nổi bật gồm thành thạo Python, SQL, Airbyte, Dagster, Redshift, PostgreSQL, kinh nghiệm làm việc với GCP, AWS, Terraform, Docker, Kubernetes và khả năng giao tiếp tiếng Anh tốt để đồng hành cùng đội ngũ quốc tế. Ưu tiên ứng viên có tư duy tự động hóa, thích giải quyết sự cố hệ thống, và thích nghi tốt với khối lượng công việc thay đổi.
About KIMEI Global
KIMEI Global was established in January 2021 by leaders with more than 10 years of experience in the software industry and over five years of working with clients in various global markets such as Japan, Korea, US, EU, Brazil, Australia, and SEA. The company's vision is to become the top trusted technology partner in the region, providing high-quality Software Development and Offshore Development Center (ODC) solutions to empower businesses, optimize operations, drive digital transformation, accelerate innovation, and achieve sustainable growth.
Having delivered over 150 projects to more than 30 global clients, KIMEI continues to expand, offering "Dedicated Team Model" and Software Development Services for global businesses seeking reliable and scalable tech solutions. The company delivers end-to-end development services with speed, excellence, and full ownership. While the headquarters are in Vietnam (Ho Chi Minh City and Hanoi), the international office is based in Japan.
Position: Senior Data & Infrastructure Engineer
Company: KIMEI Global
Location: Ho Chi Minh City, Vietnam (Remote)
Role Overview
A Senior Data & Infrastructure Engineer is needed to manage the operational and infrastructure responsibilities of KIMEI's data ecosystem. This hybrid role combines Data Engineering (70%) and DevOps/Site Reliability (30%), with a focus on maintaining high system uptime, optimizing cloud costs, and ensuring data pipeline reliability.
Core Responsibilities
- Data Pipeline Management & Maintenance
- API integration: Integrate new endpoints for Amazon SP-APIs, Shopify APIs, or any given API based on business needs.
- Pipeline Evolution: Manage new dataset onboarding, scheduling, schema updates, and backfill operations across Redshift and Postgres.
- Incident Response: Monitor, debug, and resolve issues within the data stack (Amazon SP-API, Shopify API, Airbyte, Dagster, DBT, Redshift).
- Data Integrity: Ensure synchronization across various sources and troubleshoot latency or sync failures.
- Infrastructure & DevOps
- Infrastructure as Code (IaC): Manage and provision cloud resources using Terraform.
- Cloud Operations: Maintain and optimize services across GCP and AWS, including jobs, schedulers, and server health.
- CI/CD & Automation: Build and refine automated workflows to streamline deployments and AI-driven processes.
- Performance & Monitoring
- Observability: Set up and refine monitoring/alerting systems to ensure proactive issue detection.
- Cost Optimization: Identify and implement strategies to reduce cloud spend and improve resource efficiency.
Technical Requirements
Category Must-Have Skills
- Data Stack: Airbyte, Dagster, Redshift, PostgreSQL
- Cloud Platforms: Google Cloud Platform (GCP) & Amazon Web Services (AWS)
- IaC & CI/CD: Terraform, GitHub Actions / GitLab CI, Docker
- Computing: Cloud Run, Kubernetes, Serverless workflows
- Languages: Python (Expert), SQL (High Proficiency)
Ideal Candidate Profile
- The Troubleshooter: Enjoy "under the hood" work and can find solutions to complex data and infrastructure issues.
- Context-Driven: Can handle a variety of tasks from high-level infrastructure setups to detailed Python debugging.
- English Proficiency: Strong written and verbal English skills for effective coordination with the international team.
Key Performance Indicators (KPIs)
- System Uptime: Minimize downtime for critical data syncs.
- Resolution Speed: Mean time to resolution (MTTR) for data-related incidents.
- Efficiency: Successfully reduce infrastructure costs through optimization.
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