Data Management Specialist

MOLEAC PTE. LTD.; Singapore; On-site; SGD 45,000 - 65,000; Full time

Job summary

A digital management firm in Singapore is seeking a detail-oriented Data Management Specialist to lead efforts in restructuring their digital file architecture. You'll be responsible for establishing a single source of truth, conducting audits, and improving data quality to support internal AI tools. Candidates should have strong file management skills and the ability to work collaboratively across departments. Experience in document control and relevant software is preferred.

Qualifications

• Deep understanding of Windows Explorer, shared drive hierarchies, and mass-file management techniques.
• Proven ability to convert legacy formats (specifically .msg emails) into PDF.
• Ability to analyze file contents for version control.

Responsibilities

• Audit and rationalize current shared folders.
• Support the improvement of AI generated answers with accurate documents.
• Convert Outlook Message files into accessible PDF formats.
• Act as the primary point of contact for every department.
• Focus on intensive audit and cleanup of legacy data.

Skills

Advanced File Management

Format Conversion & Extraction

Analytical Document Control

Microsoft Office Suite

Analytical Judgement

Structured & Methodical

Zero‑Error Mindset

Stakeholder Communication

Independent Coordination

Tools

Nitro PDF

Adobe Acrobat Pro

Job description

Department: IT
Reports To: Associate Manager, Web Development with dotted line to Head of IT

Role Summary

We are seeking a detail‑oriented and analytical Data Management Specialist to lead a critical restructuring of our organization’s digital file architecture. The primary objective of this role is to establish and maintain a structured, accurate single source of truth that powers both daily operations and our internal AI tools. You will act as the gatekeeper of our digital knowledge, working across all departments to separate active "Working" data from "Archived" history. By improving data quality and document governance, you will ensure that outdated or duplicated files do not interfere with AI training outcomes.

Key Responsibilities

1. Shared Folder Architecture & Data Hygiene

• Audit & Rationalization: Conduct a comprehensive audit of current shared folders to rationalize the volume of accumulated files. Design a clear separation strategy between "Active/Working" directories and "Archived/Legacy" folders to reduce data noise.
• Intelligent Version Control: Analyze file contents to distinguish between latest versions, drafts, and duplicates. You must exercise analytical judgement to ensure only the most current, authoritative data is accessible to the AI ingestion layer.
• Migration & Standardization: Physically organize and move high volumes of files into the new structure. Simultaneously, implement clear naming conventions and folder hierarchies aligned with business best practices to prevent future clutter.

2. AI Readiness & Knowledge Quality Support

• Support the improvement of Generative‑AI generated answers by ensuring that source documents used for AI reference are accurate, relevant, and current.
• Identify and flag documents that may negatively impact AI outputs due to being outdated, incomplete, or duplicated.

3. Format Standardization & Data Preparation

• Email & Attachment Processing: Systematically convert Outlook Message (.msg) files into accessible, searchable PDF formats. Crucially, extract attachments from these messages and re‑file them into the correct working folders, ensuring valuable data is not hidden inside archived emails.
• AI Readability Assurance: Ensure all converted documents are stored in standardized, machine‑readable formats (e.g., OCR‑processed PDFs, clean Word docs).
• Naming & Classification: Apply consistent naming conventions to all converted files and extracted attachments to ensure they are easily searchable by both humans and the AI.

4. Cross‑Departmental Collaboration & Validation

• Stakeholder Liaison: Act as the primary point of contact for every department. You will actively interview team leads and subject matter experts to understand their specific file usage and determine accurate retention requirements.
• Data Verification: Work with file owners to validate the "truth" of the data. You must confirm which documents are final, authoritative versions for AI ingestion, versus which are drafts or duplicates that should be archived.
• User Guidance: As the new structure is implemented, provide guidance to staff on proper file storage and naming conventions to ensure the clean structure is maintained long‑term.

5. Process Sustainability & Role Evolution

• Focus: This role is heavily focused on the intensive audit, cleanup, and restructuring of the legacy data repository.

Required Skills & Competencies

Technical & Functional Skills:

• Advanced File Management: Deep understanding of Windows Explorer, shared drive hierarchies, file extensions, and mass‑file management techniques.
• Format Conversion & Extraction: Proven technical ability to convert legacy formats (specifically .msg emails) into PDF and extract attachments into working directories. Familiarity with Nitro Pdf, Adobe Acrobat Pro or bulk conversion tools is a distinct advantage.
• Analytical Document Control: Ability to analyze file contents to distinguish between "Draft," "Final," and "Obsolete" versions without sole reliance on timestamps. Understanding of basic version control and data lifecycle practices.
• Microsoft Office Suite: High proficiency in Word, Excel, and Outlook.

Soft Skills & Attributes:

• Analytical Judgement: The ability to "read between the lines" and make informed judgments on document relevance. You must be able to distinguish between a draft, a final version, or a duplicate without needing constant supervision.
• Structured & Methodical: A systematic approach to organizing complex information. You need to handle repetitive, high‑volume tasks with patience while maintaining focus on the larger strategic goal of AI readiness.
• Zero‑Error Mindset: High level of attention to detail with zero tolerance for accidental data loss. You must ensure that while we archive old files, no critical history is deleted.
• Stakeholder Communication: Confidence to speak with HODs and team members from different departments. You must be professional and tactful when clarifying document ownership or challenging the relevance of old files.
• Independent Coordination: Ability to work autonomously on the cleanup while proactively coordinating across teams to get the answers you need.

Preferred Qualifications

• Experience in Records Management or Data Entry with an administrative focus.
• Basic understanding of how Large Language Models (LLMs) or Generative‑AI tools ingest data is a strong advantage.