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Partner with business users, architects, developers and data stakeholders to translate requirements into scalable analytics solutions.
Design, develop and optimise ETL data pipelines, data models, and integration frameworks.
Support data warehouse architecture improvements and drive best practices for data management.
Conduct data quality assessments, reconciliation processes and exception handling controls.
Troubleshoot and resolve data discrepancies across upstream and downstream systems.
Gather, analyse and validate business requirements through workshops and stakeholder engagement.
Prepare technical documentation covering functional and non-functional requirements.
Evaluate new data sources and assess integration impacts on existing platforms.
Develop dimensional data models including Star Schema and Snowflake Schema designs.
Ensure solution scalability, maintainability, governance and traceability for enterprise data platforms.
Support Power BI and SSAS environments, including deployment, performance tuning and security configuration.
Drive enterprise-scale data warehouse and BI initiatives
Exposure to modern analytics and ETL technologies
Degree holder in Computer Science, Engineering, Statistics, Mathematics, Business Management, Project Management or related disciplines.
Minimum 5 years of IT experience with exposure to data warehouse, business intelligence or data migration projects.
At least 3 years of hands-on experience with Oracle or SQL Server development.
Strong knowledge of SQL, Stored Procedures, DDL and DML programming.
Solid understanding of data modelling, data architecture and data quality management principles.
Experience designing ETL processes and enterprise data warehouse solutions.
Hands-on experience with Power BI, SSAS and dimensional modelling techniques.
Familiarity with Star Schema, Snowflake Schema and data warehouse best practices.
Knowledge of Power BI security models, including Row-Level Security.
Experience working with JSON APIs and Power Query M scripts is advantageous.
Exposure to Hadoop, Python, Java Spring Boot, Docker or OpenShift is a plus.
Strong analytical thinking, problem-solving and stakeholder management skills.
Fluent in written and spoken English and Chinese (Cantonese and Mandarin).
Our client is a leading telecommunications organisation in Hong Kong, supporting large-scale data warehouse and business intelligence platforms. They are seeking an experienced Data Analytics Engineer to strengthen their Data Warehouse team and drive data pipeline enhancement, analytics solutions, and enterprise data architecture initiatives.
Competitive monthly salary and benefits package.
All-inclusive benefits package.
Temporary role in a prominent technology setting in Kowloon.
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Partner with business users, architects, developers and data stakeholders to translate requirements into scalable analytics solutions.
Design, develop and optimise ETL data pipelines, data models, and integration frameworks.
Support data warehouse architecture improvements and drive best practices for data management.
Conduct data quality assessments, reconciliation processes and exception handling controls.
Troubleshoot and resolve data discrepancies across upstream and downstream systems.
Gather, analyse and validate business requirements through workshops and stakeholder engagement.
Prepare technical documentation covering functional and non-functional requirements.
Evaluate new data sources and assess integration impacts on existing platforms.
Develop dimensional data models including Star Schema and Snowflake Schema designs.
Ensure solution scalability, maintainability, governance and traceability for enterprise data platforms.
Support Power BI and SSAS environments, including deployment, performance tuning and security configuration.
Drive enterprise-scale data warehouse and BI initiatives
Exposure to modern analytics and ETL technologies
Degree holder in Computer Science, Engineering, Statistics, Mathematics, Business Management, Project Management or related disciplines.
Minimum 5 years of IT experience with exposure to data warehouse, business intelligence or data migration projects.
At least 3 years of hands-on experience with Oracle or SQL Server development.
Strong knowledge of SQL, Stored Procedures, DDL and DML programming.
Solid understanding of data modelling, data architecture and data quality management principles.
Experience designing ETL processes and enterprise data warehouse solutions.
Hands-on experience with Power BI, SSAS and dimensional modelling techniques.
Familiarity with Star Schema, Snowflake Schema and data warehouse best practices.
Knowledge of Power BI security models, including Row-Level Security.
Experience working with JSON APIs and Power Query M scripts is advantageous.
Exposure to Hadoop, Python, Java Spring Boot, Docker or OpenShift is a plus.
Strong analytical thinking, problem-solving and stakeholder management skills.
Fluent in written and spoken English and Chinese (Cantonese and Mandarin).
Our client is a leading telecommunications organisation in Hong Kong, supporting large-scale data warehouse and business intelligence platforms. They are seeking an experienced Data Analytics Engineer to strengthen their Data Warehouse team and drive data pipeline enhancement, analytics solutions, and enterprise data architecture initiatives.
Competitive monthly salary and benefits package.
All-inclusive benefits package.
Temporary role in a prominent technology setting in Kowloon.
Unlock job insights
Hirer responsiveness Salary match Number of applicants
#J-18808-Ljbffr
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