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Cloud Data Engineer

Singapore/Kuala Lumpur

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Role Overview:​

We are seeking a highly skilled Cloud Data/AI Engineer to design, build, and optimize data pipelines, AI-driven solutions, and cloud-based architectures. This role is ideal for individuals with strong logical and analytical thinking skills and hands-on experience with ETL processes, dashboards, and data engineering using PySpark. Whether you’re a fresh graduate eager to launch your career or an experienced professional (senior roles available for candidates with 4+ years of experience), this is an exciting opportunity to work on Generative AI innovations and AWS native technologies in a hybrid work environment.

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Key Responsibilities:​

  1. ​Data Pipeline and ETL Development:

    • Build, optimize, and manage ETL pipelines using PySpark and AWS Glue for large-scale data processing.

    • Design robust data workflows for processing structured and unstructured data.

    • Ensure data integrity and security in all stages of processing.

  2. Dashboard and Data Visualization for Data engineer:

    • Design and develop dashboards using tools like AWS QuickSight, Tableau, or Power BI.

    • Collaborate with stakeholders to create insightful visualizations for data-driven decision-making.

  3. AI/ML Model Development and Deployment for AI engineer:

    • Develop, deploy, and maintain AI/ML models using frameworks such as TensorFlow, PyTorch, or Scikit-learn.

    • Implement models on cloud platforms using AWS SageMaker and automate model training and deployment pipelines.

  4. Cloud Infrastructure and Data Management:

    • Architect and deploy scalable data solutions using AWS services like Redshift, EMR, and S3.

    • Use Infrastructure as Code tools (e.g., Terraform, AWS CDK, or CloudFormation) to automate deployments.

  5. Performance Optimization:

    • Optimize ETL pipelines, AI models, and data queries for performance, cost-efficiency, and scalability.

    • Monitor data workflows and resolve bottlenecks proactively.

  6. Explore AWS and Generative AI Innovations:

    • Gain hands-on experience with Generative AI tools and frameworks to create innovative data and AI solutions.

    • Experiment with the latest AWS native technologies to enhance data pipelines and AI projects.

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Requirements:​

  • Education: Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. Equivalent practical experience will also be considered.

  • Hands-on experience with ETL pipelines using PySpark and data transformation tools like AWS Glue.

  • Proficiency in building interactive dashboards with tools like Tableau, AWS QuickSight, or Power BI.

  • Strong programming skills in Python (preferred) or other languages for data processing and AI/ML development.

  • Familiarity with cloud platforms (AWS preferred) and services like S3, Redshift, and SageMaker.

  • Strong logical and analytical thinking skills for solving complex data problems.

  • Knowledge of SQL and database management systems.

  • Fresh graduates with a passion for cloud data engineering and AI are encouraged to apply.

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Preferred Skills:​

  • Relevant AWS Certifications (e.g., AWS Certified Data Analytics, AWS Certified Machine Learning) are a strong plus.

  • Senior candidates (4+ years) should demonstrate expertise in PySpark, dashboard development, large-scale data processing, and AI/ML model deployment.

  • Familiarity with monitoring tools for data pipelines and AI workflows.

  • Strong communication skills for collaborating across teams and presenting data insights.​

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Benefits​

  • Competitive salaries.

  • Career growth opportunities.

  • Flexible working hour.

  • Attractive benefits.

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