Product Manager

Dimensional Management Engineer

Hai Phong - Viet Nam

Information Technology & Services

Collaborate with Industrial Design (ID) and Mechanical Engineering (ME) partners to convert desired product experiences to appropriate specifications & dimensional requirements. Provide guidance on dimensioning schemes, datum selections, measurements, and GD&T application in accordance with ASME standards as well as needs of downstream assembly & system. Lead TA/VSA and then collaborate with partner teams on appropriate countermeasures to address identified risks & challenges. Coordinate Development Validations & Verifications (DEV V&Vs) planning activity and then drive supplier partners on readiness of measurement system to support DEV V&Vs and sustaining, this includes but not limit to guiding checking or holding fixture design, document measurement operation procedures, problem solving on metrology issues and measurement system qualification through correlation, gauge repeatability & reproducibility (or attribute repeatability & reproducibility for qualitative results), travel may be required. Lead the creation of DEV health dashboard and collaborate with internal & external partners for problem solving to get issues resolved to enable product ramp up on time & cost target. Work with manufacturing engineering teams and/or manufacturing vendors during the development of dimensional controls to ensure the quality tradeoff in between functionality and manufacturability. Provide guidance to other ME or ODM partners DEV team in the dimensional analysis requirements and processes. Participate in concurrent design development activities to ensure that the Dimensional Management objectives are maintained during collaborative design reviews.

Negotiation

Senior Product Manager

Ho Chi Minh - Viet Nam

No.1 Construction Tech company in Japan

• Product Management

#The Opportunity: As the promoter of product development projects at the company, you will gain experience in project management and development direction, working with the business department from project definition to requirements definition, development, testing, and release. In the future, you will be responsible for product management of the company's products.#Job Scope: This is an important position that involves understanding the characteristics of users of the service and driving product development projects while balancing the needs of product, sales, customer success, and engineers. #Product Management: Define the scope, objectives, and goals of product development. Build the product structure and process, create and promote schedules. #Development Direction: Working with product managers to organize requirements, design business processes, and define requirements. Creating and executing test and release plans. Creating explanatory materials for internal/customer use. Verifying post-release effectiveness and reporting. Create and maintain comprehensive product documentation #Development Environment: Backend: Ruby on Rails, Go, AWS, Elasticsearch, MySQL, DynamoDB, Redis, Terraform (IaC), OIDC (Authentication). Frontend: Next.js/React.js, Typescript, Vue.js/Nuxt.js. Mobile App: Kotlin, Swift, Flutter. CI/CD & DevOps: Docker, Kubernetes, CodePipeline, CodeBuild, CircleCI, GitHub Actions. Monitoring & Tools: Datadog, Sentry, Bugsnag, Swagger, ZenHub, Figma

Negotiation

Senior/ Lead Data Engineer (Data Platform / MLOps)

Ho Chi Minh, Ha Noi - Viet Nam

Information Technology & Services

You will be responsible for managing, designing, and enhancing data systems and workflows that drive key business decisions. The role is focused 75% on data engineering, involving the construction and optimization of data pipelines and architectures, and 25% on supporting data science initiatives through collaboration with data science teams for machine learning workflows and advanced analytics. You will leverage technologies like Python, Airflow, Kubernetes, and AWS to deliver high-quality data solutions. Architect, develop, and maintain scalable data infrastructure, including data lakes, pipelines, and metadata repositories, ensuring the timely and accurate delivery of data to stakeholders. Work closely with data scientists to build and support data models, integrate data sources, and support machine learning workflows and experimentation environments. Develop and optimize large-scale, batch, and real-time data processing systems to enhance operational efficiency and meet business objectives. Leverage Python, Apache Airflow, and AWS services to automate data workflows and processes, ensuring efficient scheduling and monitoring. Utilize AWS services such as S3, Glue, EC2, and Lambda to manage data storage and compute resources, ensuring high performance, scalability, and cost-efficiency. Implement robust testing and validation procedures to ensure the reliability, accuracy, and security of data processing workflows. Stay informed of industry best practices and emerging technologies in both data engineering and data science to propose optimizations and innovative solutions.

Negotiation