Senior Analyst, Data Ops & Engineering (Leading Islamic Bank in Malaysia)

Private Advertiser; Kuala Lumpur; On-site; MYR 150,000 - 200,000; Full time

Job summary

A leading Islamic bank in Kuala Lumpur is seeking a Senior Analyst for Data Ops and Engineering. This role involves designing and maintaining the bank's data ecosystem, ensuring high-quality data, and enabling self-service analytics. The ideal candidate holds a degree in a related field and has at least 3 years of experience with SQL, Python, and ETL tools. The bank offers a meaningful mission in financial inclusion, a collaborative culture, and significant opportunities for growth.

Benefits

Meaningful mission in financial inclusion

Opportunities for growth and leadership

Support for innovation and modernization

Qualifications

• Minimum 3 years of experience as a data analyst.
• Proficiency in SQL, Python, or R for data analysis.
• Experience with ETL tools like Informatica, Talend, or SSIS.
• Familiarity with data visualization tools such as MicroStrategy and Tableau.

Responsibilities

• Design and maintain the enterprise data ecosystem.
• Build and operate reliable data pipelines.
• Implement data validation and profiling frameworks.
• Collaborate with Data Governance for trusted data assets.
• Develop standardized data models for analytics.

Skills

SQL

Python

ETL tools

Data analysis

Data visualization tools

Education

Bachelor's or master's degree in computer science, data science, IT, Statistics

Tools

Informatica

Tableau

Microsoft Power BI

Job description

Senior Analyst, Data Ops & Engineering (Leading Islamic Bank in Malaysia)

Own the enterprise data, analytics and AI agenda for a leading Islamic bank—turning trusted, Shariah‑aligned data into real business value at scale.

Why this role matters

Senior Analyst/Analyst, Data Ops & Engineering is responsible for designing, developing, and maintaining the bank’s enterprise data ecosystem to ensure high-quality, trusted, and integrated data. The role encompasses data architecture, integration, and visualization to support data democratization and informed decision-making.

What you’ll do

Build and Operate Reliable Data Pipelines.

Design, automate, and maintain end‑to‑end data pipelines that deliver accurate, timely, and complete data from multiple systems to analytics and reporting platforms.

Embed DataOps practices such as CI/CD, automated testing, observability, and version control to ensure reliability, scalability, and minimal downtime.

Uphold Data Quality and Governance.

Implement data validation, reconciliation, and profiling frameworks to ensure integrity, completeness across all datasets.

Collaborate with Data Governance to maintain trusted data assets as part of the Bank’s Single Source of Truth.

Develop and Standardize Data Models.

Design standardized, scalable, and business‑aligned data models for analytical and operational purposes.

Continuously optimize models for query performance, cost efficiency, and interoperability across systems.

Enable Insight Delivery and Self‑Service Analytics.

Operationalize curated datasets into governed semantic layers for visualization and self‑service analytics.

Automate BI asset deployment and access provisioning to maintain a consistent and secure reporting environment.

Execute SIT, UAT, Acceptance, and Deployment.

Plan, coordinate, and execute System Integration Testing (SIT) and User Acceptance Testing (UAT) for data products and analytical solutions.

Ensure all deliverables meet defined acceptance and certification criteria before deployment to production.

Strengthen Collaboration and Continuous Improvement.

Act as the bridge between data engineering, analytics, and business teams to ensure seamless integration and value realization.

What success looks like (12–18 months)

Improved data architecture and quality to build a trusted Data Quality and Master Data Management.

All deliverables certified, tested, and deployed with zero critical defects; full traceability and rollback readiness achieved.

Collaboration with Business Unit to enrich deliverable value.

What you’ll bring

Bachelor’s or master’s degree in computer science/ data science/ information technology/ Statistics or related field.

Minimum 3 years of experience.

Proficiency in programming languages commonly used for data analysis, such as SQL, Python, or R.

Experience using ETL tools like Informatica, Talend, or SSIS is valuable for efficiently handling data extraction, transformation, and loading from various sources.

Familiarity with data visualization tools such as MicroStrategy, Tableau, and Microsoft Power BI and statistical analysis techniques.

Knowledge of data storage requirements and design warehouse architecture and experience with SQL/NoSQL databases and data mapping.

Benefits that matter to leaders

Mission with meaning: Advance financial inclusion and customer trust through Shariah‑aligned, ethical data and AI.

Enterprise scope: Board‑level mandate, bank‑wide impact, and sponsorship to modernise platforms and practices.

Talent and culture: Build and lead a top‑tier data organisation with strong craft, stewardship and growth pathways.

Platform for innovation: Run pragmatic experiments where it counts; standardise where it scales.

How to express interest

If you’re energized by building a trusted, Shariah‑aligned, AI‑ready data ecosystem—and converting analytics into outsized business value—we’d love to hear from you.

Your application will include the following questions

• How many years' experience do you have as a data analyst?
• How many years' experience do you have as a data scientist?
• Which of the following statements best describes your right to work in Malaysia?
• Have you worked in a role which requires experience with machine learning?
• What's your expected monthly basic salary?
• Which of the following types of qualifications do you have?
• How many years' experience do you have as a SQL BI Developer?
• How many years' experience do you have as a SQL Specialist?