Engineering Manager
JOB DESCRIPTION
JOB REQUIREMENT
WHAT'S ON OFFER
CONTACT
Job Summary
Company Type:
Product
Technical Skills:
.NET, Python, Frontend
Location:
Ho Chi Minh - Viet Nam
Working Policy:
Salary:
Negotiation
Job ID:
J01395
Status:
Close
Related Job:
Senior Technical Project Manager – Automotive Chiplet Software
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Outsource
- Project Management
- Embedded
Engage with international stakeholders from various sectors and partners to accomplish project objectives Take accountability for meeting project targets and KPIs within specified deadlines, budget, and ensuring customer satisfaction Collaborate with program and project management, internal sub-project teams, external partners, and customers to establish project targets and provide regular project updates Assist in securing new customers by creating custom presentations related to software domains in close collaboration with project, product management, and sales Support the development process for Tier 2 suppliers to ensure successful implementation of projects, including applying project management tools and defining software development processes Participate in setting up an efficient software development process and defining interfaces to adapt to the customer-specific ACS project tool chain Collaborate with technical and business experts to define work products for the development team aligned with original equipment manufacturer (OEM) and Automotive Chiplet System (ACS) platform requirements Assist in customer demonstrations and provide high-quality technical documentation for projects, ensuring compliance with international standards.
Negotiation
View detailsEngineering Manager (Data Platform)
Ho Chi Minh - Viet Nam
Offshore
- Data Engineering
- Management
Agile Team Leadership: Guide and coach Agile teams to uphold engineering standards, manage sprint backlogs, clarify responsibilities, ensure code quality, enforce development guardrails, and drive rigorous testing practices. Agile Data Delivery: Oversee Agile execution across data platforms, maintaining excellence in data quality, testing, code review practices, CI/CD pipelines, documentation, and operational readiness. Cross-Functional Collaboration: Partner with data architects, product managers, analytics teams, platform engineers, and governance stakeholders to deliver data capabilities aligned with business priorities. Roadmap Ownership: Lead the execution of the data engineering roadmap, balancing immediate delivery needs with long-term platform sustainability. Architecture & Design: Contribute to the design of data platform architecture across ingestion, transformation, storage, and consumption layers. Engineer Development: Coach engineers to become T-shaped professionals, capable of working across batch processing, streaming, analytics engineering, and platform operations. Technical Debt Remediation: Own and prioritize the resolution of technical and data debt, including legacy pipelines, performance bottlenecks, and data quality issues. Modern Practices: Stay current with evolving data engineering tools, methodologies, and patterns-particularly within the Databricks ecosystem. Lifecycle Accountability: Ensure end-to-end ownership of data solutions, from design and build through deployment, monitoring, and ongoing support. Team Empowerment: Foster self-sufficient, disciplined teams accountable for the reliability and resilience of data products. Process Excellence: Lead initiatives to enhance data delivery through automation, observability, and operational best practices. Continuous Improvement: Inspire teams to innovate, experiment, and embrace continuous delivery as part of their culture. Career Growth: Drive career development for data engineers, partnering with HR to manage performance and define growth pathways.
Negotiation
View detailsSoftware Engineer
Ho Chi Minh - Viet Nam
Product
- Backend
- Devops
- Cloud
- Kubernetes
- Python
- Javascript
- Typescript
Create and develop the API Platform with a focus on reliability, performance, and providing a top-tier developer experience Deploy and enhance AI/ML models in scalable, production environments in collaboration with research and applied ML teams Manage and advance a contemporary, cloud-native infrastructure stack utilizing Kubernetes, Docker, and infrastructure-as-code (IaC) tools Ensure platform dependability by designing and implementing telemetry, monitoring, alerting, autoscaling, failover, and disaster recovery mechanisms Contribute to developer and operations workflows, encompassing CI/CD pipelines, release management, and on-call rotations Work collaboratively across teams to implement secure APIs with fine-grained access control, usage metering, and billing integration Continuously enhance platform performance, cost-efficiency, and observability to accommodate scaling and serve users globally.