Data Engineer  

  • Design and Develop Data Pipelines: Create and maintain efficient, reliable, and scalable data pipelines that extract, transform, and load (ETL) data from diverse sources into AWS data storage systems.
  • Data Modeling and Architecture: Design and implement data models for data warehousing and data lakes on AWS, ensuring data integrity, performance, and scalability.
  • AWS Cloud Infrastructure: Utilize various AWS services such as Amazon S3, Amazon Redshift, AWS Glue, Amazon EMR, Amazon RDS, and others to build data solutions.
  • Data Transformation and Processing: Develop data transformation processes, including data cleansing, enrichment, and aggregation, to ensure data accuracy and consistency.
  • Performance Optimization: Identify and implement performance optimization techniques to enhance data processing speed and reduce latency in data pipelines.
  • Data Security and Compliance: Ensure that data handling practices comply with relevant data security and privacy regulations. Implement security measures to protect sensitive data.
  • Monitoring and Troubleshooting: Monitor data pipelines, data jobs, and data storage systems for issues and troubleshoot any data-related problems to ensure smooth data flow.
  • Documentation: Create and maintain technical documentation for data engineering processes, data models, and data pipelines.
  • Collaboration and Communication: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions that meet business needs.
  • Continuous Improvement: Stay updated with the latest AWS services and data engineering best practices to propose and implement improvements to the existing data infrastructure.

  • Bachelor's degree in Computer Science, Engineering, or a related field. A Master's degree is a plus.
  • Proven experience as a Data Engineer for at least 1-2 years, specifically working with AWS data services and related technologies.
  • Strong knowledge of AWS services such as Amazon S3, Amazon Redshift, AWS Glue, Amazon EMR, Amazon RDS, and others.
  • Proficiency in programming languages such as Python, SQL, and familiarity with data manipulation frameworks/libraries.
  • Hands-on experience with data modeling, data warehousing concepts, and building data pipelines using ETL tools
  • Familiarity with data governance, data security, and data privacy best practices.
  • Excellent problem-solving skills and the ability to work independently as well as part of a team.
  • Strong communication skills to effectively collaborate with cross-functional teams and convey technical concepts to non-technical stakeholder

  Employment Type:  Permanent (Full Time)

  Spoken Language:  Malay, English

  Written Language:  Malay, English