Location: Hong Kong Island (Hybrid work arrangement)
Relevant experience: 4-7 years
Role Overview
We are seeking a Data Engineer (Data Integration) to design, develop, and maintain scalable data ingestion and integration solutions that enable reliable and efficient data movement into a modern data platform. The role will work closely with business stakeholders, source system owners, and technology teams to ensure data is ingested, transformed, and made available for analytics, reporting, and operational use cases.
Key Responsibilities
Design, develop, and maintain robust data ingestion pipelines to integrate data from diverse sources, including POS systems, ERP platforms, APIs, databases, cloud storage, and third-party applications.
Collaborate with business and technical stakeholders to understand source system structures, data requirements, and integration needs.
Implement, monitor, and support data integration processes to ensure data is ingested accurately, transformed efficiently, and delivered reliably for downstream consumption.
Develop and optimize batch, streaming, and near real-time ingestion workflows with a focus on performance, scalability, reliability, and cost efficiency.
Manage and maintain data source connectivity, mappings, metadata, and lineage documentation to support governance and data discoverability.
Perform root cause analysis and troubleshoot data integration issues, implementing corrective and preventive measures where necessary.
Contribute to continuous improvement initiatives by identifying opportunities to enhance integration frameworks, processes, and operational efficiency.
Ensure adherence to data engineering standards, security requirements, and best practices across all integration activities.
Technical Skills & Experience
Data Integration Engineering
Hands-on experience developing scalable data ingestion and integration pipelines using tools such as Azure Data Factory, Microsoft Fabric Dataflows, Databricks, or equivalent integration technologies.
Strong understanding of modern data integration patterns and architectures.
Multi-Source Connectivity
Experience integrating data from a variety of sources, including relational and NoSQL databases, APIs, flat files, cloud-based storage, ERP systems, and third-party platforms.
Proficient in authentication methods, schema mapping, data transformations, and integration design.
ETL/ELT Development
Proven experience designing and implementing ETL/ELT solutions supporting batch, streaming, and real-time data ingestion.
Familiarity with schema evolution, error handling, orchestration, and monitoring best practices.
Data Quality & Validation
Ability to implement data validation, quality controls, reconciliation processes, and exception handling to ensure data accuracy and integrity.
Strong troubleshooting and analytical skills in resolving data-related issues.
Performance & Cost Optimization
Experience optimizing pipeline performance, scalability, and resource utilization.
Understanding of cloud-based cost management principles and best practices.
Documentation & Governance
Ability to maintain comprehensive documentation of data mappings, integration processes, technical specifications, and data lineage.
Understanding of data governance, metadata management, and data cataloguing concepts.
Modern Data Platforms
Familiarity with modern cloud data platforms and architectures, including Databricks, Microsoft Fabric, Lakehouse, Data Warehouse, and related integration services.
Understanding of data engineering practices within enterprise-scale environments.
Domain Experience (Preferred)
Experience working with POS, retail, consumer goods, or similar transactional data environments is advantageous.
Ability to quickly learn new business domains and understand data flow dependencies across enterprise systems.
Core Competencies
Analytical & Detail-Oriented
Strong attention to detail with a focus on data accuracy, completeness, and consistency throughout the integration lifecycle.
Effective communicator who can work closely with business stakeholders, source system owners, architects, and development teams to deliver integration solutions.
Problem Solving
Demonstrates a proactive approach to identifying, investigating, and resolving data integration challenges.
Ownership & Accountability
Takes responsibility for the end-to-end delivery, quality, and support of data integration solutions.
Adaptability & Continuous Learning
Embraces changing technologies, evolving business requirements, and continuous improvement opportunities.
Demonstrates curiosity and a commitment to professional development and technical excellence.
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Relevant experience: 4-7 years
Role Overview
We are seeking a Data Engineer (Data Integration) to design, develop, and maintain scalable data ingestion and integration solutions that enable reliable and efficient data movement into a modern data platform. The role will work closely with business stakeholders, source system owners, and technology teams to ensure data is ingested, transformed, and made available for analytics, reporting, and operational use cases.
Key Responsibilities
Design, develop, and maintain robust data ingestion pipelines to integrate data from diverse sources, including POS systems, ERP platforms, APIs, databases, cloud storage, and third-party applications.
Collaborate with business and technical stakeholders to understand source system structures, data requirements, and integration needs.
Implement, monitor, and support data integration processes to ensure data is ingested accurately, transformed efficiently, and delivered reliably for downstream consumption.
Develop and optimize batch, streaming, and near real-time ingestion workflows with a focus on performance, scalability, reliability, and cost efficiency.
Manage and maintain data source connectivity, mappings, metadata, and lineage documentation to support governance and data discoverability.
Perform root cause analysis and troubleshoot data integration issues, implementing corrective and preventive measures where necessary.
Contribute to continuous improvement initiatives by identifying opportunities to enhance integration frameworks, processes, and operational efficiency.
Ensure adherence to data engineering standards, security requirements, and best practices across all integration activities.
Technical Skills & Experience
Data Integration Engineering
Hands-on experience developing scalable data ingestion and integration pipelines using tools such as Azure Data Factory, Microsoft Fabric Dataflows, Databricks, or equivalent integration technologies.
Strong understanding of modern data integration patterns and architectures.
Multi-Source Connectivity
Experience integrating data from a variety of sources, including relational and NoSQL databases, APIs, flat files, cloud-based storage, ERP systems, and third-party platforms.
Proficient in authentication methods, schema mapping, data transformations, and integration design.
ETL/ELT Development
Proven experience designing and implementing ETL/ELT solutions supporting batch, streaming, and real-time data ingestion.
Familiarity with schema evolution, error handling, orchestration, and monitoring best practices.
Data Quality & Validation
Ability to implement data validation, quality controls, reconciliation processes, and exception handling to ensure data accuracy and integrity.
Strong troubleshooting and analytical skills in resolving data-related issues.
Performance & Cost Optimization
Experience optimizing pipeline performance, scalability, and resource utilization.
Understanding of cloud-based cost management principles and best practices.
Documentation & Governance
Ability to maintain comprehensive documentation of data mappings, integration processes, technical specifications, and data lineage.
Understanding of data governance, metadata management, and data cataloguing concepts.
Modern Data Platforms
Familiarity with modern cloud data platforms and architectures, including Databricks, Microsoft Fabric, Lakehouse, Data Warehouse, and related integration services.
Understanding of data engineering practices within enterprise-scale environments.
Domain Experience (Preferred)
Experience working with POS, retail, consumer goods, or similar transactional data environments is advantageous.
Ability to quickly learn new business domains and understand data flow dependencies across enterprise systems.
Core Competencies
Analytical & Detail-Oriented
Strong attention to detail with a focus on data accuracy, completeness, and consistency throughout the integration lifecycle.
Effective communicator who can work closely with business stakeholders, source system owners, architects, and development teams to deliver integration solutions.
Problem Solving
Demonstrates a proactive approach to identifying, investigating, and resolving data integration challenges.
Ownership & Accountability
Takes responsibility for the end-to-end delivery, quality, and support of data integration solutions.
Adaptability & Continuous Learning
Embraces changing technologies, evolving business requirements, and continuous improvement opportunities.
Demonstrates curiosity and a commitment to professional development and technical excellence.
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