- Hong Kong Hong Kong
GL Technologies (Hong Kong) Limited Hiring! Full Time Data Analyst Engineer in Hong Kong - Ricebowl
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Job Description
Responsibilities
Job Responsibilities
Data Middle Platform Development
Participate in the overall planning, development, and continuous optimization of the data middle platform. Align business data needs with underlying data capabilities, and promote unified data standards, metric definitions, and data processes across departments.
Analysis Dimensions and Metric System Development
Work closely with business teams to define and align core analysis dimensions, metric definitions, calculation logic, and business rules. Build reusable metric systems and data dictionaries to support analytics needs across multiple business lines.
Business Data Analysis
Conduct daily data analysis based on business priorities and deliver actionable insights and recommendations, including but not limited to:
Sales Data: Sales volume, orders, conversion, repeat purchases, returns, etc.
Cost Data: Costs, expenses, profit, gross margin structure, etc.
Marketing Data: Advertising ROI, campaign performance, channel contribution, user growth, etc.
Dashboard and Report Development
Design, configure, and continuously improve dashboards and reports using tools such as Superset and Feishu Bitable. Ensure report accuracy, timeliness, and usability, and establish standardized reporting templates.
AI-Driven Analytics Efficiency
Proficiently use AI tools to support data analysis, including natural language data querying, automatic SQL generation, data interpretation, and report generation. Explore and implement AI-driven efficiency improvements in analytics scenarios, such as automated querying, intelligent insights, reporting assistants, and automated report generation.
Qualifications
Required
Education: Bachelor’s degree or above in Statistics, Mathematics, Computer Science, Information Engineering, Economics, or a related field.
Experience: 1+ years of experience in data analysis, data middle platform development, or a related role.
SQL: Proficient in writing complex SQL, including window functions, multi-table joins, and performance tuning; familiar with PostgreSQL or other mainstream databases.
Data Modeling: Familiar with DBT or similar ETL / data modeling tools, with an understanding of data layering, model design, and metric development.
BI Tools: Proficient in Superset or other mainstream BI tools, such as Tableau, Power BI, or Metabase.
Reporting Tools: Familiar with Feishu Bitable or similar multidimensional spreadsheet and reporting tools.
Metadata Management: Understanding of OpenMetadata or similar metadata management tools, including data lineage, metric management, and data asset management.
Business Understanding: Solid understanding of sales, cost, and marketing data, with the ability to extract business insights and drive business improvements through data.
AI Tool Usage: Proficient in using AI tools for data analysis, such as AI-powered querying, natural language SQL generation, and AI-assisted reporting, and able to apply them effectively to improve work efficiency.
Preferred
Experience building a data middle platform or metric system from scratch.
Familiarity with e-commerce or cross-border e-commerce business.
Python data analysis experience, such as Pandas, NumPy, statistical analysis, and data visualization.
Experience implementing AI-driven efficiency projects, such as AI-powered querying, intelligent reporting assistants, or natural language metric search.
Proven experience helping business teams make data-driven decisions.
Full-time
Data Middle Platform Development
Participate in the overall planning, development, and continuous optimization of the data middle platform. Align business data needs with underlying data capabilities, and promote unified data standards, metric definitions, and data processes across departments.
Analysis Dimensions and Metric System Development
Work closely with business teams to define and align core analysis dimensions, metric definitions, calculation logic, and business rules. Build reusable metric systems and data dictionaries to support analytics needs across multiple business lines.
Business Data Analysis
Conduct daily data analysis based on business priorities and deliver actionable insights and recommendations, including but not limited to:
Sales Data: Sales volume, orders, conversion, repeat purchases, returns, etc.
Cost Data: Costs, expenses, profit, gross margin structure, etc.
Marketing Data: Advertising ROI, campaign performance, channel contribution, user growth, etc.
Dashboard and Report Development
Design, configure, and continuously improve dashboards and reports using tools such as Superset and Feishu Bitable. Ensure report accuracy, timeliness, and usability, and establish standardized reporting templates.
AI-Driven Analytics Efficiency
Proficiently use AI tools to support data analysis, including natural language data querying, automatic SQL generation, data interpretation, and report generation. Explore and implement AI-driven efficiency improvements in analytics scenarios, such as automated querying, intelligent insights, reporting assistants, and automated report generation.
Qualifications
Required
Education: Bachelor’s degree or above in Statistics, Mathematics, Computer Science, Information Engineering, Economics, or a related field.
Experience: 1+ years of experience in data analysis, data middle platform development, or a related role.
SQL: Proficient in writing complex SQL, including window functions, multi-table joins, and performance tuning; familiar with PostgreSQL or other mainstream databases.
Data Modeling: Familiar with DBT or similar ETL / data modeling tools, with an understanding of data layering, model design, and metric development.
BI Tools: Proficient in Superset or other mainstream BI tools, such as Tableau, Power BI, or Metabase.
Reporting Tools: Familiar with Feishu Bitable or similar multidimensional spreadsheet and reporting tools.
Metadata Management: Understanding of OpenMetadata or similar metadata management tools, including data lineage, metric management, and data asset management.
Business Understanding: Solid understanding of sales, cost, and marketing data, with the ability to extract business insights and drive business improvements through data.
AI Tool Usage: Proficient in using AI tools for data analysis, such as AI-powered querying, natural language SQL generation, and AI-assisted reporting, and able to apply them effectively to improve work efficiency.
Preferred
Experience building a data middle platform or metric system from scratch.
Familiarity with e-commerce or cross-border e-commerce business.
Python data analysis experience, such as Pandas, NumPy, statistical analysis, and data visualization.
Experience implementing AI-driven efficiency projects, such as AI-powered querying, intelligent reporting assistants, or natural language metric search.
Proven experience helping business teams make data-driven decisions.
Full-time
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