Senior Executive, Data Architecture & Engineering

KEY RESPONSIBILITIES

Data extraction services

Execute ad-hoc, monthly and quarterly data extraction services as required by CTOS internal/external clients and in accordance with services SLA

Perform QA activities related to client data services

Execute data analysis to provide insight for internal/external needs

Automate recurrent data related activities

Ensure zero non-compliances on process audit on data security and compliance

Data pipeline development and operationalization

Design and build data pipelines to ingest data from multiple sources and implement quality processes

Design processes to create data insight, data features and operationalize analytics models

Maintain and develop the cloud services relating to data pipelines

Operationalize data pipelines for automated and semi-automated execution

Implement reporting of data universe, data quality across the organization

Implement Dashboard and reports based on stakeholder requirements

Build control and monitoring points to maintain data integrity: reliability, completeness, cleanliness

Ensure zero non-compliances on process audit on data security and compliance

Maintain documentation of processes and workflows

Data platform innovation

Support key initiatives including migration of CTOS data services to the cloud

Implement solutions ranging from proof of concepts to fully productive applications

WHAT DOES IT TAKE TO BE SUCCESSFUL

Qualifications

A Bachelor’s Degree, Post Graduate Diploma, or Professional Degree in Computer Science, Information Technology, or a related field

Work Experience

Minimum 4 years of experience with ETL/ELT tools

Minimum 4 years of experience working with data platforms

Minimum 4 years of experience in dashboard development and automation

Minimum 4 years of experience with cloud services (AWS preferred)

Experience working in the financial industry is a plus



Skills & Competencies

Strong knowledge of data platforms, data pipelines, and data-related development (e.g., Hadoop, Spark, Jupyter, cloud-native services)

Proficient in cloud services and cloud-native data tools (AWS preferred)

Skilled in programming languages and tools for data pipelines (e.g., SQL, Python/Pandas/PySpark)

Proficient with automation and monitoring tools (e.g., shell scripting, Airflow)

Experienced with ETL tools such as Talend and/or cloud-native services like EMR, AWS Glue, EC2, S3

Capable of troubleshooting data issues

Able to implement data reporting solutions using platforms such as Grafana, Power BI, QuickSight

Excellent written and verbal communication skills, including English

Understanding of financial data systems (e.g., CCRIS, SSM, Angkasa, Idaman) is a plus

Interpersonal & Cross-Cultural Skills

Design thinking

Outstanding communication and interpersonal abilities

Able to convey complex technical concepts in a clear, accessible manner