Expired

Project Manager

星瀚科技·IT / E-Business

Expired

Replied to 7 talents in 7 days

HK work permit required

5 to 10 yrs exp

Higher Diploma or Associate Degree

5 days per week

HK $20K-30K/Month

Job Description

Project Manager
Job Responsibilities

Lead IT-type projects through their entire life cycle, including requirement analysis, planning and design, resource coordination, progress control, risk assessment and closing delivery, ensuring that the project is completed on time, within budget and of high quality.
Deeply involved in cloud platform (such as AWS, Azure or GCP) related project technical architecture discussion and implementation, and collaborate with development and operations teams to promote cloud-native application (Cloud-Native) deployment and optimization.
Coordinate large-scale data project data governance, platform construction (such as Hadoop, Spark, Data Lake), ETL process design and visualization report integration, supporting business decision-making and data-driven operations.
Integrate AI technology scenarios (such as machine learning model deployment, NLP application integration, AIoT system connection, etc.), coordinate data scientists and engineering teams, and promote the transformation of AI solutions from validation (PoC) to mass production (Production).

Work requirements

Have more than 6 years of IT project management practical experience, familiar with PMBOK or PRINCE2, etc. project management methodological knowledge, holding PMP, CSM or ACP certification is preferred.
Solid understanding of cloud service core concepts and implementation experience, familiar with containerization (Docker/Kubernetes), microservice architecture, CI/CD pipelines, and mainstream cloud platform management interfaces and API integration.
Have practical experience in the big data technology stack, understand the role and collaboration logic of tools such as HDFS, Spark SQL, Flink, Kafka, Airflow in projects.
Have basic knowledge of AI technology application scenarios, be able to communicate with technical teams on model training, data annotation, inference deployment, monitoring and maintenance, etc., and have cross-domain collaboration and translation abilities.

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