Data Engineer

Sun Hung Kai Properties Limited; Hong Kong; On-site; HKD 420,000 - 660,000; Full time

Job summary

Sun Hung Kai Properties Limited is seeking a data analytics professional with 4-5 years of experience in applying technical skills to data engineering, BI and customer analytics. You will handle multi-source data, perform cleansing, standardization and quality checks, and develop automated data processing and dashboards.

The role requires strong Python and SQL, advanced Excel, and good English/Chinese communication.

Qualifications

• Bachelor’s degree or above in Computer Science, Information Systems, Business Analytics, Data Analytics, Data Science, Decision Science, or related disciplines.
• 4-5 years of experience in applying technical skills and programming, data engineering, databases, or BI/data processing.
• Solid experience in handling data from multi-sources and in different forms, including data cleansing, structuring, standardization, and quality checks.
• High proficiency in Python, SQL, other scripting, and use of AI tools for database set-up and analytics.
• Advanced Excel and knowledge of SPSS is an advantage.
• Experience setting up and maintaining datasets, documentation, and workflow processes.
• Strong English and Chinese communication skills; analytical and problem-solving abilities.

Responsibilities

• Execute design, set-up and maintain structured and unstructured research data and customer-centric analysis databases from multiple sources.
• Define database architecture, data structures, fields and groupings, cleansing rules, and workflow across survey datasets.
• Automate data processing, templates, reports and dashboards using programs or scripts.
• Clean, validate and standardize multi-sourced data to ensure quality and consistency.
• Write and update data books, data structures, definitions, reporting templates and guidelines.
• Provide technical support and guidance to team members for optimal data handling.

Skills

Python

SQL

Data analysis

BI/data processing

AI tools

Excel

English & Chinese communication

Education

Bachelor's degree+ in CS/IS/Analytics

Tools

SPSS

Data processing tools

Job description

• 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

Responsibilities

• 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