CN-Shenzhen Standard - 40 Hours (China) 40 Permanent The incumbent, Data Analytics Project Manager, Chief Data Office of the Information Technology Division, is an important and strategically aligned role for developing data analytics capabilities and solutions on our enterprise data platform.

• Lead cross-functional teams and manage end-to-end responsibilities of data engineering projects, from inception to deployment
• Collaborate with business stakeholders to deliver data platform capabilities, prioritizing requirements basing on business benefits and protection against data risks
• Project manage data initiatives, tracking progress and risks against scope, schedule and costs, in coordination with business and tech units
• Promote compliant and quality reuse of data on enterprise platform, through incremental delivering functionalities in data lifecycle, including data access control, data lineage, data quality, data analytics etc.
• Manage third party data products and vendors for deployment on the data platform
• Implement cloud and open source capabilities to enable end-to-end data capabilities
• Effectively use hybrid project management techniques, applying agile tools within SDLC phases
• Coordinate with data engineering function in their efficient use of technical tools, internal resources and skills, optimizing technical synergies and efficiency across initiatives

• Bachelor’s degree in technology, engineering, or related disciplines
• 10 or more years of working experience in IT development or project management, preferably having good track record in large enterprises. VP position requires stronger technology and management experiences
• Well versed with SDLC project disciplines, experience with Agile methodologies and leading cross-functional teams
• Solid technical background with hands-on experience in software development and data related technologies, such as multi-tiered service oriented architecture, data modelling and data visualization
• Good coverage and understanding of enterprise data architecture requirements and end to end technology stack
• Experience in Jupyter Hub or equivalent data scientist workbench and deployment of multi-tenant architecture
• Familiar with native cloud technologies, e.g. AWS EKS, EFS
• Experience in data security and data management tools, e.g. LDAP, OAuth, Keycloak, AWS Lake Formation, AWS Data Catalog, Open Metadata
• Familiarity with data management, data governance and data quality standards
• Excellent communication and influencing skills
• PMP, PRINCE2 or Agile certification is an advantage