Assistant Manager - Data Analytics & Engineering

• Bachelor’s degree or above, preferably in Computer Science, Information Systems, Business Analytics, Data Analytics, Data Science, Decision Science, or any related disciplines
• Minimum 8 years of experience in databases establishment and development, data analytics, data engineering, automation, reporting, writing user requirements, definitions and specifications etc., preferably in handling different types of data, survey data and customer analytics environments
• Solid experience in handling data from multi-sources and in different forms, including data cleansing, structuring, standardization, database management, standard setting, quality controls, and governance
• Proficiency in Python, SQL, other relevant programming or scripting, and mastering use of AI tools for database architecture, data analytics and processing, as well as automation
• Familiar with Excel (advanced functions), and SPSS is an advantage
• Experience in designing, establishing and owning datasets/database, documentation, and writing workflow processes
• Proven verbal and written English and Chinese proficiency, with good communication skills
• Strong analytical, numerical, logic, and problem-solving skills, as well as business acumen
• Self-motivated, responsible, independent, attention to details, organized, and positive work attitude

Responsibilities:

• Lead, design, establish, own, and maintain structured and unstructured research data and customer-centric analysis databases from various sources, including self-owned, research, voice/audio, social media data etc.
• Manage and execute databases, data analytics, automation and reporting related projects
• Establish and define database architecture, data structures, fields and groupings, cleansing rules, research data coding/grouping skeleton and execution programming, and workflow across survey datasets and integrate into unified, well-organized, and trusted databases
• Automate workflow, templates, reports and dashboards and related, by using programs or scripts or other methods and tools that can efficiently meet the business needs of data analysis
• Review, clean, validate and standardize multi-sourced data to ensure quality, consistency, and reliability
• Propose to use, deploy, upgrade, and maintain any new or existing platforms that link with databases
• Write and update user requirements, database schemas/books, data architecture, data field definitions, data types, reporting templates and framework, data handling and tasks procedures, workflow, automation rules, guidelines and standards, data analytics and database documentation
• Provide technical support with contingency and usage guidance to team members for the best practices
• Perform ad-hoc tasks and other related projects assigned to align business needs