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

Jobstreet Malaysia; Kuala Lumpur; On-site; MYR 60,000 - 80,000; Full time

Job summary

A leading Islamic bank in Kuala Lumpur is looking for a Senior Analyst in Data Ops & Engineering to manage enterprise data and analytics initiatives. The successful candidate will design and maintain data ecosystems, ensuring reliability and integrity of data to support informed decision-making. A degree in a relevant field and at least 3 years of experience are required, with proficiency in SQL and ETL tools enhancing eligibility. This position offers opportunities to innovate within the enterprise's data strategy.

Benefits

Innovative work environment

Opportunities for professional growth

Impactful mission and responsibilities

Qualifications

• Minimum 3 years of experience in a relevant role.
• Proficiency in programming languages commonly used for data analysis.
• Familiarity with data visualization tools and statistical analysis techniques.

Responsibilities

• Build and operate reliable data pipelines.
• Design and maintain end-to-end data pipelines.
• Implement data quality frameworks for completeness across datasets.
• Operationalize curated datasets into governed semantic layers.

Skills

SQL

Python

R

Informatica

Talend

SSIS

MicroStrategy

Tableau

Microsoft Power BI

Education

Bachelor’s or master’s degree in computer science, data science, information technology, Statistics

Tools

ETL Tools

SQL/NoSQL databases

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.
• 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.
• 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.
• 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.
• 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, and 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 on data storage requirements and design warehouse architecture and experienced 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.