Data Engineer | Cloud & Data Pipelines | Contract

NEXBRIDGE RECRUITMENT PTE. LTD.

Singapore

On-site

SGD 90,000 - 140,000

Full time

8 days ago
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Job summary

NEXBRIDGE RECRUITMENT PTE. LTD. is seeking a Data Engineer to design, build and maintain production-grade ETL/ELT data pipelines. You will integrate data from databases, APIs, files, SaaS platforms and streaming sources, and develop streaming and event-driven data processes.

You will work with cloud environments (AWS/Azure), implement data quality controls, and collaborate with cross-functional teams to deliver trusted datasets and analytics-ready data products.

Qualifications

  • 3–5 years of experience in Data Engineering, Cloud Data Engineering, Analytics Engineering, Software Engineering or related fields.
  • At least 2 years of hands‑on experience building and operating production data pipelines.
  • Strong experience with Python and SQL.
  • Experience with ETL/ELT, data transformation and data modelling.
  • Experience with AWS and/or Azure data capabilities.
  • Experience integrating data from APIs, databases, enterprise systems or streaming sources.
  • Knowledge of batch, incremental, CDC and/or event-driven data pipelines.
  • Experience working with cloud and/or hybrid environments.
  • Familiarity with Terraform/OpenTofu, CI/CD and automated testing.
  • Strong analytical and problem-solving skills.

Responsibilities

  • Design, build and maintain production-grade ETL/ELT data pipelines.
  • Integrate data from databases, APIs, enterprise applications, files, SaaS platforms and streaming sources.
  • Develop batch, incremental, CDC, streaming and event-driven data pipelines.
  • Transform and structure raw data into reliable and trusted datasets.
  • Design and maintain data models, data stores, data lakes and analytical datasets.
  • Implement data validation, reconciliation and data-quality controls.
  • Monitor data pipeline performance, freshness, reliability and processing latency.
  • Build reusable datasets and data products for reporting, dashboards and analytics.
  • Support data and analytics use cases, including machine-learning initiatives where required.
  • Work with application, platform and infrastructure teams to establish reliable data integrations.
  • Apply security, governance, access control and data-retention requirements.
  • Support production incidents, troubleshooting and continuous improvement.

Skills

Data Engineering
Python
SQL
ETL/ELT
AWS/Azure
CI/CD
Data pipelines
Analytics

Tools

Terraform/OpenTofu
CI/CD tooling
Automated testing

Job description

Job Responsibilities
  • Design, build and maintain production-grade ETL/ELT data pipelines.
  • Integrate data from databases, APIs, enterprise applications, files, SaaS platforms and streaming sources.
  • Develop batch, incremental, CDC, streaming and event-driven data pipelines.
  • Transform and structure raw data into reliable and trusted datasets.
  • Design and maintain data models, data stores, data lakes and analytical datasets.
  • Implement data validation, reconciliation and data-quality controls.
  • Monitor data pipeline performance, freshness, reliability and processing latency.
  • Build reusable datasets and data products for reporting, dashboards and analytics.
  • Support data and analytics use cases, including machine-learning initiatives where required.
  • Work with application, platform and infrastructure teams to establish reliable data integrations.
  • Apply security, governance, access control and data-retention requirements.
  • Support production incidents, troubleshooting and continuous improvement.
  • 3–5 years of experience in Data Engineering, Cloud Data Engineering, Analytics Engineering, Software Engineering or related fields.
  • At least 2 years of hands‑on experience building and operating production data pipelines.
  • Strong experience with Python and SQL.
  • Experience with ETL/ELT, data transformation and data modelling.
  • Experience with AWS and/or Azure data capabilities.
  • Experience integrating data from APIs, databases, enterprise systems or streaming sources.
  • Knowledge of batch, incremental, CDC and/or event-driven data pipelines.
  • Experience working with cloud and/or hybrid environments.
  • Familiarity with Terraform/OpenTofu, CI/CD and automated testing.
  • Strong analytical and problem-solving skills.
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