Assistant Manager - Data Analytics & Engineering

任职要求
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

职责描述
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