Data Engineering and Analytics

NSEARCH GLOBAL PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

NSEARCH GLOBAL PTE. LTD. is sourcing for a Data Engineering and Analytics role on behalf of a major APAC client.

The ideal candidate has 3-5 years of experience in data engineering or related disciplines and hands-on experience building and operating production-grade data pipelines. Requirements include proficiency with AWS and/or Azure native data capabilities, data integration from APIs, databases, files, or streaming sources, and strong software-engineering practices such as CI/CD and IaC.

Qualifications

• 3-5 years in data engineering, cloud data engineering, analytics engineering, software engineering, or a related discipline.
• 2+ years designing, building, and operating production-grade data pipelines.

Skills

Data engineering

Cloud data engineering

Analytics engineering

Software engineering

Data pipelines

ETL/ELT

Data modelling

Data quality

AWS/Azure

API/data integration

Batch/CDC/Streaming pipelines

Hybrid integration

CI/CD & IaC

Logging/Monitoring

Python

SQL

Job description

Data Engineering and Analytics

Our client, one of Asia-Pacific's leading organizations is looking for:

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
• AWS/Azure-native logging, streaming, storage, search and data services
• Enterprise servers, networks, applications, databases, virtualised infrastructure, and log sources
• Python, SQL, ETL/ELT, batch, incremental, CDC, streaming, and event-driven patterns