Junior, Data Engineer

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Guidelines On Tranglos Look and Feel – Kuala Lumpur, Kuala Lumpur

• Drive the implementation and optimization of centralized data repositories and data lake architectures, supporting enterprise-wide analytics and reporting.
• Identify, diagnose, and resolve data-related issues, ensuring data quality, integrity, and availability for downstream analytics and business applications.
• Apply advanced data modeling techniques to solve real-world business challenges, ensuring data consistency, integrity, and performance.
• Provide advanced support and troubleshooting for data pipelines, ETL/ELT processes, and data integration workflows across cloud and on-prem environments.
• Enhance and mentor others in organizational, communication, and analytical skills, fostering a collaborative and data-driven engineering culture.
• Gain exposure to the end-to-end machine learning lifecycle, from experimentation to production, by enabling robust and scalable data access for model training and inference.

Department : Data
Division : Technology

You will be exposed to:

• Drive the implementation and optimization of centralized data repositories and data lake architectures, supporting enterprise-wide analytics and reporting.
• Identify, diagnose, and resolve data-related issues, ensuring data quality, integrity, and availability for downstream analytics and business applications.
• Apply advanced data modeling techniques to solve real-world business challenges, ensuring data consistency, integrity, and performance.
• Provide advanced support and troubleshooting for data pipelines, ETL/ELT processes, and data integration workflows across cloud and on-prem environments.
• Enhance and mentor others in organizational, communication, and analytical skills, fostering a collaborative and data-driven engineering culture.
• Gain exposure to the end-to-end machine learning lifecycle, from experimentation to production, by enabling robust and scalable data access for model training and inference.

Key responsibilities:

• Develop, optimize, and maintain robust data pipelines(ETL/ELT) across both on-premise and cloud environments
• Work closely with business and technical teams to ensure that data mapping aligns with business rules and reporting needs
• Maintain data lake and data warehouse solutions
• Develop detailed reports and documentation of incidents and resolutions to contribute towards continuous improvement processes within the team
• Create and maintain data mapping documents to define the relationships between source data and target schemas.
• Develop and support the ingestion of data from multiple sources into a centralized data repository or data lake.
• Perform basic data cleaning, transformation, and validation to ensure data quality and integrity.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 2 years of experience in data engineering, data warehousing, or big data environments
• Strong understanding of data structures, performance tuning, and optimization.
• Strong proficiency in SQL and one or more programming languages (Python, Java, or Scala).
• Ability to troubleshoot and improve complex data workflows.
• Experience designing systems for scalability, reliability, and maintainability.
• Strong communication and documentation skills.
• Solid understanding of data governance, security, and compliance principles.
• Strong communication and documentation skills.
• Exposure to BI tools such as Power BI, Tableau, or Looker for data consumption and visualization.
• Exposure to Machine Learning projects implementation
  Nice to have: Experience with streaming platforms