【全球智慧製造】資料工程師(Infrastructure)
面議（經常性薪資達4萬元或以上） 40000元
新北市新店區
1~2年工作經驗
【全球智慧製造】
你知道Garmin的智慧工廠嗎? 你知道火星上出現過Garmin的產品嗎? 你知道飛行員總是配戴Garmin的手錶上天空嗎?
全球智慧製造服務計畫(GSMS)透過AI、機構、電控、資料科學、IoT、大數據等技術，將智慧製造系統，即時控制與調整全球生產系統，且在地化支援亞洲、美洲、歐洲多個國家
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【Introduction】
Data Engineering Team is part of Garmin‘s Process Integration Department, we are looking for engineer to join our data infrastructure team. Cooperate with Data Engineer to build, maintain and optimize data platform and data pipeline. Our mission is to drive stability, scalability and efficiency for the PI data ecosystem and build a manufacturing data center in Garmin.
【Responsibilities】
1. Maintain High Availability: Ensure the stability and uptime of the data platform by continuously optimizing monitoring and alerting processes.
2. Platform Administration: Manage and optimize Dremio Data Lakehouse engine to drive performance tuning and resource management.
3. Data Governance & Security: Enhance data security and auditability by implementing robust Access Control Lists (ACL) and managing comprehensive service audit logs.
4. Service Reliability & Operations: Participate in on-call rotations to handle data service anomalies following established SOPs.
5. Architectural Evolution: Research and integrate new technologies to continuously evolve the data platform architecture for future scalability and challenges.
【Requirements】
1. Problem-Solving Skills: Ability to perform deep-dive root cause analysis and resolve complex technical issues through a logical, step-by-step approach.
2. Data Infrastructure & Storage: Extensive experience in managing and maintaining NoSQL/Messaging services (Hadoop, Kafka, Elasticsearch, MQTT, Redis) / Object Storage (S3, MinIO) or RDB (PostgreSQL, MySQL, MSSQL, Oracle)
3. Advanced Monitoring: Experience in building and managing monitoring frameworks for data pipelines or database services using Prometheus/Grafana or Zabbix
4. Programming Language: Proficiency in Python; familiarity with Linux operating systems and shell scripting.
5. Containerization: Hands-on experience with container technologies (Docker Compose, Docker Swarm, or Kubernetes).
6. English Communication: Good verbal and written communication skills in English; comfortable conducting technical discussions with service support and participating in meetings with overseas colleagues.
【Bonus Points】
1. Data Lakehouse Platforms: Familiarity with Dremio, Denodo, Snowflake, or Databricks for data virtualization or distributed SQL execution.
2. Incident Management: Prior experience with on-call (on-duty) rotations or familiarity with incident management tools such as PagerDuty.
3. Kubernetes Proficiency: Experience deploying or managing services on Kubernetes, with a specific understanding of the challenges of Database Containerization.
4. Infrastructure as Code (IaC): Familiarity with IaC tools (e.g., Ansible) to automate data platform deployments.
5. AI Integration: Practical experience in AI Agents or LLM-based workflows.
展開
