Associate Data Engineer
Working Hour
Regular Hours
Monday - Friday
Business Area
Strategy & Analytics
Location
Malaysia - Kuala Lumpur
Working Hour
Regular Hours
Monday - Friday
Location
Malaysia - Kuala Lumpur
Business Area
Strategy & Analytics
Description

Primary Objective:

  • Acquiring and collecting raw data from various sources, ensuring the efficient and accurate transfer of data into storage systems.
  • Operationalize Analytics Data Pipeline from Data Lake into Gold Zone and other Downstreams
  • Documenting data engineering processes, workflows, and data architectures.
  • Implementing automation scripts or tools to streamline repetitive data engineering tasks.
  • Improving efficiency through the use of automation in data workflows.
  • Keeping up-to-date with industry trends, emerging technologies, and best practices in data engineering.
  • Seeking opportunities for continuous learning and skill development in data engineering tools and technologies.

Key Responsibilities:

• Developing and maintaining ELT/ETL processes for moving data between systems, optimizing ELT/ETL workflows for performance and efficiency.
• Cleaning and preprocessing data to make it suitable for analysis, implementing data transformation processes to convert raw data into a structured, usable format.
• Monitoring data pipelines for performance and identifying bottlenecks.
• Troubleshooting and resolving issues related to data processing and integration.
• Creating documentation to facilitate knowledge transfer and support ongoing maintenance.
• Able to effectively engage and communicate with stakeholders & other business units

 

Requirements

Requirements:
Bachelor Degree - Bachelor degree or above in Computer Science, Economics, Finance, Mathematics, Statistics or equivalent..

  • A min. of 0-3 years experience in Data Engineering (banking & insurance experience is a plus)
  • Knowledge of relational databases and a good command of SQL
  • Understanding of basic data pipeline design, including data extraction, transformation, and loading processes.

 

 

 

 

Strong analytical and problem-solving skills.

  • Proficiency in programming languages: SAS, Python, SQL etc.
  • Big Data Technologies: Hands-on experience with Hadoop, Spark or similar technologies for large-scale data processing.
  • Data Quality and Testing: Understanding of data quality checks, monitoring, and testing procedures.
  • Basic knowledge of data visualization tools (e.g. Tableau, Power BI).

Understanding of statistical analysis, machine learning concepts, modeling conceptual ideas and database management.

Benefits

Dental, Education support, Miscellaneous allowance, Medical, Loans, Sports (e.g. Gym), Parking, Vision, Regular hours, Mondays - Fridays, Casual Business Wear, Performance Based Rewards

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