Lead Data Engineer

2 weeks ago

Ho Chi Minh City, Ho Chi Minh, Vietnam Adecco's Client Full time ₫800,000,000 - ₫1,000,000,000 per year

Location:
Tan Binh, Ho Chi Minh City, Vietnam

Salary range:
70-75M VND gross

Job Summary:

We are looking for a Senior DevOps & Data Engineer to lead the design and implementation of scalable data pipelines and infrastructure, with a strong focus on Model Context Protocol (MCP). This role combines leadership, system architecture, and hands-on engineering to support data-driven applications and model lifecycle management.

Key Responsibilities:

DevOps Responsibilities:


• Lead the development and maintenance of CI/CD pipelines for model deployment and data services.


• Manage infrastructure automation using tools like Terraform, Ansible, or Kubernetes.


• Ensure system reliability, scalability, and security across environments.


• Monitor and optimize cloud/on-prem resources and performance.


• Collaborate with engineering and data science teams to streamline deployment workflows.

Data Engineering Responsibilities:


• Design and implement robust data pipelines that support MCP-based model context workflows.


• Build and maintain ETL/ELT processes for structured and unstructured data.


• Ensure data integrity, lineage, and traceability across model contexts.


• Integrate data pipelines with model registries, versioning systems, and metadata stores.


• Work closely with model developers to ensure seamless data-model interaction.

Leadership Responsibilities:


• Lead and mentor a team of DevOps and Data Engineers.


• Define and enforce best practices for infrastructure and data pipeline development.


• Collaborate with cross-functional teams to align technical solutions with business and modeling goals.


• Provide technical guidance and hands-on support when needed.

Requirements:


• 5 years of experience in DevOps
OR/AND
Data Engineering roles.

We are open to candidate with strong experience in one stack: DevOps or Data; and willing to learn the other.


• Strong understanding of Model Context Protocol (MCP) and its application in model lifecycle management.


• Experience with data pipeline tools (e.g., Apache Airflow, Spark, Kafka) and orchestration frameworks.


• Proficiency in scripting languages (Python, Bash, etc.) and infrastructure tools (Docker, Kubernetes).


• Familiarity with model registries, metadata management, and version control systems.


• Bachelor's degree in Computer Science, Data Engineering, or related field.

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