Senior Data Engineer

2 days ago

Kuala Lumpur, Kuala Lumpur, Malaysia axrail Full time $60,000 - $120,000 per year

We are seeking a highly skilled
Cloud Data 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. This is an exciting opportunity to work on Generative AI innovations and AWS native technologies in a hybrid work environment.

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.

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.

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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