Senior Business Systems & Data Analyst

Salary: RM 6,700 – RM 7,000 per month

Role Overview

This hybrid role bridges Business & Systems Analysis, EMS and Enterprise CRM Architecture, and Advanced Data Analytics / Business Intelligence (BI). You will be responsible for translating institutional needs into automated workflows, managing core enterprise architectures, and turning raw data into strategic, prescriptive insights for university leadership.

Key Responsibilities

1. Requirements Gathering & Systems Analysis

• Stakeholder Workshops: Lead requirement gathering sessions with Sales, Marketing, Support, and Academic departments to translate vague needs into technical requirements.

• Functional Specifications: Define and document functional specifications, user stories, and comprehensive acceptance criteria for system enhancements.

• Gap Analysis: Evaluate existing CRM, EMS, and LMS functionalities against evolving business objectives to recommend upgrades or integrations

2. CRM Architecture & System Administration

• Lifecycle Management: Manage the complete lifecycle of the enterprise CRM platform (e.g., Salesforce, Microsoft Dynamics, HubSpot), including user access, custom objects, and custom permission sets.

• Workflow Automation: Design and configure complex workflow automations, validation rules, processes, and flows to streamline sales, marketing, and university operations.

• System Integrations: Oversee API integrations between the CRM, EMS, third-party tools, ERP systems, billing systems, and external marketing databases.

• Troubleshooting: Diagnose and resolve advanced technical CRM platform bugs, system performance lags, and data sync errors.

3. Business Process Optimization

• Process Mapping: Analyze current-state operations to identify operational bottlenecks and design future-state automated system workflows.

• User Acceptance Testing (UAT): Coordinate UAT sessions, defining test scripts and ensuring system outputs perfectly match initial analysis requirements.

4. Data Engineering & Analytics Architecture

• Data Pipelines: Design and implement end-to-end data pipelines in collaboration with data engineering teams to ensure clean, structured data.

• Data Modeling: Design data models and schema mappings that align with broader enterprise architectures and reporting requirements.

5. Business Intelligence & Reporting

• KPI Dashboards: Extract and model data from multiple internal systems to build interactive Tableau or Power BI dashboards for corporate decision-making.

• Performance Tracking: Construct and maintain live dashboards detailing the operational performance of different university business units and key information systems.

6. Advanced Analytics & Data Science

• Statistical Forecasting: Apply regression, cluster analysis, and decision trees to historical institutional data to forecast enrollment trends, student retention, and revenue streams.

• Lifecycle Analytics: Conduct deep-dive cohort and customer analytics, including lead funnel management, trend forecasting, and Customer Lifetime Value (CLV) modeling.

• A/B Testing: Design, execute, and analyze A/B tests for marketing campaigns, application funnels, and student engagement strategies.

7. Data Governance, Security & Compliance

• Data Quality: Enforce data governance policies to preserve data quality, clean duplicate records, and ensure uniform metadata standards.

• Data Dictionary: Establish and maintain a centralized business data dictionary and data catalog to unify metric definitions across all departments.

• Regulatory Compliance: Safeguard system compliance with global and regional data protection regulations like GDPR, CCPA, or PDPA.

• Access Auditing: Audit system access logs routinely to guarantee that sensitive student, customer, financial, and personal data remains highly secure.

8. Leadership, Training & Innovation

• Change Management: Create training documentation and run educational workshops for end-users to maximize university-wide EMS/CRM feature adoption.

• Technology Evaluation: Evaluate new technologies and run Proof of Concepts (PoCs) for emerging data analytics and CRM artificial intelligence tools.

• Technical Translation: Partner with business units to interpret analysis results and translate raw technical data into meaningful, strategic recommendations.

• Prescriptive Modeling: Deliver data-backed simulations and scenario analyses to move beyond descriptive reporting and guide strategic institutional planning.

Job Requirements & Qualifications

Education & Certifications

• Degree: Bachelor’s degree in Computer Science, Business Analytics, Information Systems, Data Science, or a closely related analytical field.

• Preferred Certifications: Certified CRM Administrator (e.g., Salesforce Certified Admin), or Data Analytics credentials (e.g., Power BI Data Analyst, Tableau Desktop Certified).

Experience

• Overall IT Experience: Minimum of 5–7+ years of professional IT experience.

• Domain Experience: At least 3+ years directly spent conducting business/systems analysis, managing enterprise CRM architecture, and building deep-dive data pipelines.

• Methodology: Proven track record of leading software development lifecycle (SDLC) processes from initial analysis through deployment.

Technical Skills

• CRM Platforms: Expert-level administration in Salesforce, Microsoft Dynamics 365, Merrito, or Freshsales.

• BI & Visualization Tools: Hands-on dashboard creation experience in Power BI, Tableau, or Looker Studio.

Soft Skills

• Analytical Mindset: Exceptional problem-solving skills with a strict, methodical approach to system logic and business requirements.

• Stakeholder Management: Ability to manage expectations and confidently negotiate technical boundaries with non-technical business leaders.

• Communication: Clear verbal and written presentation skills to effectively document technical systems and pitch process modifications.