As a System Engineer, you will operate large-scale big data platforms across hybrid (on-premises and cloud) environments, enabling reliable analytics and data-driven use cases. You will work closely with data engineers, data scientists, infrastructure, security, and business stakeholders to ensure data quality, platform stability, and operational excellence.This role focuses on building, running, and optimizing production-grade data platforms and pipelines, with strong ownership of infrastructure, automation, reliability, and operations.
Key Responsibilities
- Design, implement, and manage scalable data platform infrastructure and pipelines across on-premises and cloud environments.
- Own the end-to-end platform lifecycle, including architecture design, deployment, operations, performance optimization, and reliability engineering.
- Maintain and support data platform clusters and nodes (compute, storage, networking), ensuring high availability and optimal performance.
- Provision, configure, and manage cloud-based data services such as AWS S3, Redshift etc.
- Monitor platform health, performance, and capacity implement observability, alerting, and operational runbooks to ensure system reliability.
- Support and optimize ETL/ELT pipelines, ensuring reliable data ingestion, transformation, and delivery.
- Operate and maintain data storage platforms (on-premises and cloud), ensuring durability, scalability, and cost efficiency.
- Implement and enforce security best practices, including IAM, VPC configurations, encryption, backup strategies, and disaster recovery.
- Ensure compliance with data governance and regulatory requirements (e.g., PDPA) in collaboration with infrastructure and security teams.
- Collaborate with data engineers, data scientists, and cross-functional stakeholders to align platform capabilities with business and analytical needs.
- Develop and maintain technical documentation, including system architecture, data flows, configurations, and operational procedures.
