jobs in Manpower Staffing Services (Malaysia) Sdn Bhd

Manpower Staffing Services (Malaysia) Hiring! Full Time Data Engineer in , Earn up to SGD 10,000 - Ricebowl

SGD3,500 - SGD10,000 Per Month

Singapore

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Working Location

  • Singapore Singapore

Job Description

Responsibilities

About the Role

As a Senior Data Engineer, you will focus on designing, building, and maintaining scalable data solutions that support business needs and AI applications. You will play a key role in:

Data Pipeline & Architecture Development

  • Build and optimize automated data pipelines for ingesting, transforming, and processing large datasets.
  • Design efficient data architectures that support analytics, machine learning, and real-time applications.

Cloud Migration & AI Enablement

  • Support cloud migration efforts, transitioning on-premises data workflows to cloud-based platforms like Databricks.
  • Collaborate with data scientists to improve feature selection, feature engineering, and enable end-to-end AI workflows from model training to deployment and monitoring.

CI/CD & Automation

  • Develop CI/CD pipelines to streamline data pipeline deployments and ensure stable, automated workflows.
  • Improve monitoring and observability to maintain system reliability.

Collaboration & Business Impact

  • Work with data scientists, product teams, and platform engineers to align data solutions with business objectives.
  • Ensure data quality, security, and compliance with industry standards.
  • Contribute to best practices in data governance, documentation, and automation.

Qualifications & Skills

  • Degree holder of Information Technology, Mathematics or Statistics with least 3 years of experience in data engineering.
  • Expert in Python, Java, SQL, Linux Shell.
  • Experience in UNIX environment, Git Flow, CI/CD automation, Jenkins, Bitbucket.
  • Hands-on experience with Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi), Spring Boot, etc. to build big data products & platforms.
  • Proficiency with a modern cloud or hybrid-cloud stack (AWS, Databricks, Cloudera, etc).
  • Experience in building and deploying production-level data-driven applications and data processing workflows or pipelines.

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