Data Engineer
Summary
Data Engineer designing, building, and operating production-grade ETL/ELT data pipelines across on-premises and cloud environments (AWS/Azure), integrating diverse data sources and delivering trusted datasets for analytics and reporting.
Our client, one of Asia-Pacific’s leading organizations is looking for:
Data Engineer
Responsibilities:
- Design, build, and operate production-grade data pipelines for data extraction, ingestion, transformation, and loading (ETL/ELT)
- Integrate data from on-premises systems, enterprise applications, APIs, databases, SaaS platforms, files, streams, cloud services, and other operational data sources
- Develop batch, incremental, change-data-capture(CDC), streaming, and event-driven ingestion patterns based on source-system and business requirements
- Build transformation pipelines that clean, enrich, standardise, join, aggregate, and structure raw data into trusted datasets
- Design secure and resilient mechanisms for transferring and synchronising data between on-premises, GCC, AWS, Azure, and other approved environments
- Design pipelines for failure handling, retry, recovery, idempotency, scalability, and changing data volumes
- Automate pipeline deployment, configuration, testing, and operation
- Design and maintain cloud-native and hybrid datastores, data lakes, and analytical datasets
- Develop data models that provide consistent representations of enterprise, operational, and asset information
- Design data architectures spanning on-premise infrastructure and cloud platforms
- Build trusted datasets and reusable data products for applications, dashboards, operational reporting, and analytics
Requirements:
- Minimum 3–5 years of experience in data engineering, cloud data engineering, analytics engineering, software engineering, or a related discipline
- At least 2 years of hands-on experience designing, building, and operating production-grade data pipelines
- Demonstrated experience with data extraction, ingestion, ETL/ELT, transformation, data modelling, and data quality
- Experience using AWS and/or Azure native data capabilities
- Experience integrating data from APIs, databases, enterprise systems, files, or streaming sources
- Experience implementing batch, incremental, CDC, and/or event-driven data pipelines
- Experience working with on-premises and/or cloud environments, with an understanding of hybrid integration patterns
- Experience applying software-engineering practices such as version control, automated testing, CI/CD, monitoring, and Infrastructure as Code to data solutions
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Interested applicants can also email CV at asmita@nsearchglobal.com (for faster processing, please state the exact job / position title applied “Data Engineer"
Only shortlisted candidates will be notified.
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EA License Number: 10C3636
EA Personnel Name: Chauhan, Asmita
EA Personnel Registration Number: R1980706
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