Data Engineer
Posted Updated 7
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Summary
In-house Data Engineer at Sun Hung Kai Properties in Hong Kong: design, build and maintain multi-source research and customer-analytics databases, define architecture, cleansing rules and workflows, and automate processing, reports and dashboards using Python, SQL and AI tools.
Requirements:
- Bachelor’s degree or above, preferably in Computer Science, Information Systems, Business Analytics, Data Analytics, Data Science, Decision Science, or any related disciplines
- 4-5 years of experience in applying technical skills and programming, data engineering, databases, or BI/data processing, 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, standard setting, and quality checks etc.
- High proficiency in Python, SQL, other relevant programming or scripting, and use of AI tools for database set-up, processing, data analytics and automation
- Have skill in Excel (advanced functions), and knowledge of SPSS is an advantage
- Experience in setting up and maintaining datasets, 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
- Execute the design, set-up 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.
- Work to 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 data processing, templates, reports and dashboards and related by using programs or scripts
- Clean, validate and standardize multi-sourced data to ensure quality, consistency, and completeness
- Write and update data books, data structure, data field definitions, reporting template and framework, data handling and tasks procedures, data cleansing rules, workflow, and any guidelines needed
- Provide technical support with contingency and usage guidance to team members for the best practices
- Perform ad-hoc tasks and other related projects as assigned to align business needs