Data Engineer: Cloud Pipelines, Analytics & Data Products

FPT Asia Pacific; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

FPT Asia Pacific is seeking a Data Engineering & Analytics Engineer to own the data lifecycle—from source systems through ingestion, transformation, modelling, quality, and serving—enabling dashboards, analytics, and ML use cases.

You will design and operate production-grade pipelines, integrate data across on-prem and cloud, and collaborate with platform engineers and application teams to deliver reliable data products.

Qualifications

• 3–5 years of experience in data engineering, analytics engineering, or related field.
• Hands-on experience designing, building, and operating production-grade data pipelines.
• Experience with data extraction, ingestion, transformation, and quality controls.
• Experience with AWS and/or Azure native data capabilities.
• Experience integrating data from APIs, databases, files, or streaming sources.
• Experience implementing batch, incremental, CDC, and/or event-driven data pipelines.

Responsibilities

• Design, build, and operate production-grade data pipelines for ETL/ELT
• Integrate data from on-premises systems, APIs, databases, and cloud services
• Develop batch, streaming, and CDC ingestion patterns
• Build transformation pipelines to create trusted datasets
• Design secure, scalable data transfers across environments
• Automate deployment, testing, and operation of pipelines
• Develop data models and data contracts for downstream consumers
• Maintain data lineage and metadata for traceability

Skills

Data pipelines

ETL/ELT

Cloud data engineering

Data modelling

CI/CD for data

Tools

AWS

Azure

Job description

FPT Asia Pacific is seeking a Data Engineering & Analytics Engineer to own the data lifecycle—from source systems through ingestion, transformation, modelling, quality, and serving—enabling dashboards, analytics, and ML use cases.

You will design and operate production-grade pipelines, integrate data across on-prem and cloud, and collaborate with platform engineers and application teams to deliver reliable data products.