EIM Data Analyst – Discovery & Profiling

Role Overview

We are seeking an experienced EIM Data Analyst specialising in Discovery & Profiling to join our team. The successful candidate will play a key role in identifying, analysing, and profiling data assets to support business value drivers, processes, and data products. This role requires advanced business analysis skills, strong data management expertise, and the ability to deliver actionable insights across the information lifecycle.

Minimum Requirements

• Bachelor’s degree or equivalent in Informatics, Information Systems, Computer Science, or related field (e.g., BCom Informatics, BSc Information Systems, BSc Informatics, BTech).
• Data Management Certification (e.g., DAMA CDMP) advantageous.
• Minimum eight years’ experience in business analysis.
• Minimum five years’ experience in Information Management Business Analysis.
• Solid exposure to Agile methodology.

Key Skills & Competencies

• Advanced knowledge of Information Lifecycle Management (ILM).
• Proficient in basic software applications (MS Word, Excel, PowerPoint, Internet, email).
• Skilled in using Data Quality tools.
• Strong analytical thinking and problem-solving abilities.
• Ability to understand and analyse business processes.
• Excellent verbal and written communication skills.
• Facilitation and workshop skills.
• Quality orientation and attention to detail.
• Negotiation and interpersonal relationship-building skills.
• Customer loyalty focus.
• Strong team player and motivated self-starter.
• Enterprising and proactive approach.

Key Deliverables

• Develop business cases and business analysis work plans.
• Prepare Business Requirements Specification and Functional Requirements Specification documents.
• Create Information Matrix, User Stories, and Change Request documents (where applicable).
• Participate in Quality Assurance and User Acceptance Testing.
• Produce Business Analysis Measure and Feedback Reports.
• Review training documentation.

Scope of Services

• Apply data discovery mechanisms to establish data assets within the context of business value drivers, processes, and data products.
• Identify and profile data assets to determine sensitivity, quality, context of use, and legislative aspects.
• Implement standards, guidelines, processes, and procedures for data analysis.
• Establish relationships between data elements and assess their business impact.
• Conduct data analysis to categorise data and information.
• Apply data valuation techniques to determine business importance and probability of reuse.
• Generate regular reports, deliver actionable insights, and provide timely status updates to support data domain management.
• Provide inputs on legislative prescripts, sensitivity classifications, access/authorisation rules, etc., as data transitions from source to destination and at rest.