[Semiconductor Transformation] Data-Ops Architect

We are looking for an experienced AI Data Infrastructure Engineer / Data Platform Architect to build the foundational data architecture behind enterprise-wide AI transformation.

What You’ll Do (Responsibilities)

• Design and maintain highly available SQL and NoSQL database infrastructure, including PostgreSQL and MongoDB.
• Build and optimize object storage solutions such as MinIO for unstructured data, model artifacts, and multimedia assets.
• Participate in or lead the modernization of on-premise AI/data infrastructure, including the adoption of platforms such as Databricks.
• Build observability infrastructure using technologies such as Elasticsearch, Grafana Loki, and ClickHouse.
• Establish robust IAM / RBAC, backup, HA, and disaster recovery mechanisms.
• Collaborate closely with AI Application Engineering, Data Engineering, and MLOps teams.
• At Lead / Architect level, define the broader technical roadmap across Data Engineering → AI Infrastructure → MLOps.

The actual scope and architectural ownership will vary according to seniority.

What You’ll Bring (Requirements)

• Hands-on experience in Data Infrastructure, Data Platform, or Backend Architecture.
• Strong knowledge of relational and NoSQL databases, particularly PostgreSQL and MongoDB.
• Experience with Object Storage, such as MinIO or equivalent cloud-native/on-premise solutions.
• Familiarity with modern Observability stacks, including Elasticsearch, Grafana Loki, or ClickHouse.
• Strong Linux, networking, and infrastructure security fundamentals.
• Understanding of IAM / RBAC, high availability, backup, and disaster recovery.
• Experience with Databricks, Spark, DataOps, or MLOps is highly valued.
• Semiconductor / IC Design experience is a plus.

What Sets This Company Apart (About the Company)

This is an opportunity to join an established publicly listed semiconductor technology company undergoing a major internal AI transformation.

Rather than simply maintaining existing data systems, this team is building the underlying infrastructure required to make enterprise AI scalable and production-ready.

The organization is particularly open on seniority: strong hands-on engineers can deepen their technical expertise, while experienced candidates can take ownership at Principal, Tech Lead, or Architect level.

What’s Next (Call to Action)

If your experience sits at the intersection of Data Infrastructure, Data Platform, MLOps, Observability, or System Architecture, I’d be happy to share more about the opportunity.

📍 Taipei / Hsinchu (preferred, first)
🏠 Flexible working arrangement
🎯 Senior / Principal / Tech Lead / Architect

Reach out for a confidential discussion.