Devops/Cloud Engineer
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Job Summary
Company Type:
Outsource
Technical Skills:
Devops, Google Cloud
Location:
Ho Chi Minh - Viet Nam
Working Policy:
Hybrid
Salary:
Negotiation
Job ID:
J01766
Status:
Close
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Senior DevOps Engineer
Ho Chi Minh - Viet Nam
Product
- Devops
- Cloud
- Kubernetes
Manage VM/Cloud Infrastructure: Ensure that web servers and cloud services (AWS, GCP) are stable and perform optimally. Manage both on-prem and cloud-based infrastructure following DevSecOps best practices, including network design and segmentation Develop and Maintain Scripts and Tools: Write and maintain scripts (bash, python) to automate routine tasks and improve system efficiency. Build and Contribute to Our Monitoring System: Set up and manage monitoring systems using Prometheus and Grafana to track system performance and send alerts. Prepare CI/CD Pipelines: Implement and maintain automated deployment pipelines using GitLab CI, ArgoCD, and FluxCD. Design and Optimize Infrastructure: Design and optimize the infrastructure to ensure system stability, minimize downtime, and enhance overall performance. Web Server and Platform Management: Manage web server configurations and security, including Nginx, Kubernetes ingress, load balancers, DNS, WAF, and firewall rules, ensuring high availability and secure operations. Collaborate with Development Teams: Work closely with development and production teams to streamline deployment processes and resolve system and security-related issues.
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View detailsData Experience Lead
Ho Chi Minh - Viet Nam
Product
- Data Science
- Management
Train pods in designing, building, deploying, and maintaining Data Products based on established playbooks. Simplify and translate platform playbooks into actionable user guides. Assist teams transitioning into new Data Mesh roles (DPO, Steward, Data Architect, Analytics Engineer, etc.). Provide hands-on support for early-wave or complex Data Products. Make data products and platform accessible and engaging for all staff across the organization. Develop a digital enablement portal including guides, checklists, templates, and videos. Create structured training pathways and capability improvement programs for all affected staff/users. Generate clear visual materials such as diagrams, flows, web-style docs, and promotional videos to aid adoption and understanding. Facilitate onboarding, workshops, roadshows, Q&A sessions, town hall presentations, and demos. Offer structured guidance across ingestion patterns, medallion design, semantics, quality, and metrics to ensure consistency in a mesh environment. Execute or coordinate targeted POCs for pods needing specialized help. Identify and communicate reusable patterns back to the Data Mesh Platform Team. Organize Showcases to create visibility, excitement, and promote reuse. Oversee the end-to-end user experience design for the Data Mesh Platform, aiming for clarity, trust, and ease of use. Shape how users discover, understand, and interact with data products across domains. Maintain UX standards in partnership with the customer-facing UX Design team. Take a deeply user-centric approach to drive change through intuitive and guided technology. Engage with end users to understand needs and gather insights. Integrate continuous feedback loops and iterate quickly to improve platform usability. Ensure all Mesh Experience features support adoption and reinforce the "data-as-a-product" mindset. Maintain active channels for communication and updates. Communicate expectations, standards, and timelines clearly. Highlight wins and success stories to build momentum. Curate relevant external content to support the transformation. Monitor progress of rollout, leader boards, and raise blockers with appropriate stakeholders. Utilize data to highlight platform adoption, culture change, wins, and challenges. Produce clear and compelling summaries on adoption progress for decision making. Manage end user feedback and be the link between users and the platform team.
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View detailsData Scientist Lead
Ho Chi Minh - Viet Nam
Outsource
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Creating robust ETL/ELT data pipelines for structured and unstructured data Developing interactive dashboards and visualizations for effective communication of insights Evaluating, deploying, and evaluating machine learning and/or generative AI models Applying statistical analysis and mathematical modeling to extract insights from complex datasets Working with various teams to deliver data-driven solutions Creating and maintaining scalable ML pipelines and APIs for real-time and batch inference Ensuring best practices in model versioning, reproducibility, observability, and governance (MLOps) Staying updated with AI/ML trends and contributing to projects involving semantic search, knowledge graphs, or retrieval-augmented generation as necessary.