Working Hour
Regular Hours
Monday - Friday
Business Area
Strategy & Analytics
Malaysia - Kuala Lumpur
Working Hour
Regular Hours
Monday - Friday
Malaysia - Kuala Lumpur
Business Area
Strategy & Analytics

Primary Objective:

•    Data Management for structured and unstructured data for Group Analytics.


•    Design, maintain, and improve data pipeline for customization of integration & visualization tools, databases, and analytical systems. 


•    Create and maintain optimal data pipeline architecture.


•    Assemble large, complex data sets that meet functional / non-functional business requirements.


•    Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.


•    Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.


•    Create data tools for analytics and data scientist team members that assist them in building and optimizing related use cases.

Key Responsibilities:

•    Gather and process raw data at scale.
•    Design and develop data applications using selected tools and frameworks as required and requested.
•    Read, extract, transform, stage and load data to selected tools and frameworks as required and requested.
•    Collaborate with data stakeholders and stewards on the verification and the accuracy of the information collected.
•    Provide technical lead to Data Owners and Stewards on data definition, data lineage changes by supporting intake process, performing impact analysis, and conducting domain specific profiling.
•    Write, deploy and maintain software to build, integrate, manage, maintain, and quality-assure data, and responsible for deploying secure and well-tested software that meets privacy and compliance requirements; develops, maintains and improves CI / CD pipeline
•    Custom integration with various banking systems, data warehouses, and analytics systems.
•    Setup of data-access or visualization tools for data scientists such as data science workbench
•    Develop and implement analytics use case to yield business value from data and insight
•    Extracts and transforms structured and unstructured big and small data to generate features, derive impactful insight, visualise information, and support impactful decision-making
•    Design of data pipeline and implement data ingestion from end-to-end to Big Data repositories.
•    Applies best practices in modular architecture, loosely coupled design, and agile development / continuous deployment software engineering principles
•    Design and implement modern data pipelines to extract, clean and process data in batch and real-time from different data sources.
•    Demonstrates efficiency through contributing to and applying bank-wide best practices in analytics and data
•    Develops technical architecture for data applications and analytics platforms (together with relevant agile team)
•    Human-centred design (together with digital team)
•    Data Management & Data Governance for Big Data Platform



Requirements: Degree/Master in IT, Computer Science or related discipline

  • Preferred level of Experience (by years/function/industry): 
  • Min. 2 years’ experience in analytics related roles (banking experience is a plus)
  • Minimum 2-4 years in data engineering areas or big data engineering fields with hands-on experience in ETL/ELT with Big Data Technology.
  • M
  • Hands-on experience designing, planning, implementing, maintaining and documenting reliable and scalable data infrastructure and data products in complex environments.
  • Experience designing and implementing large-scale distributed system
  • Experience with data pipeline and workflow management tools, as well relational SQL and NoSQL databases


§ Agile development and DevOps operating practices

§ Listening and communication/storytelling

§ Critical and evaluative thinking

§ Proactive approach with ability to work independently



§ View of what data is needed to be collected, analyzed across business solutions



§ Technical leadership in data and platform design


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