Master Data Manager

Vector Logistics; Midrand; On-site; ZAR 500 000 - 700 000; Full time

Job summary

A leading logistics company in Midrand seeks a Data Manager to oversee the lifecycle of master data across business systems and ensure compliance with data governance standards. The role involves collaborating with various teams to enhance data quality and reporting solutions. The successful candidate will have at least 5 years of experience in data management, knowledge of SAP, and the ability to lead a team. This full-time position offers a chance to drive innovation within the organization.

Benefits

Competitive salary

Career development opportunities

Qualifications

• 5+ years of experience in data management or similar roles.
• Strong knowledge of data governance principles and practices.
• Ability to lead and develop a team effectively.

Responsibilities

• Oversee the complete lifecycle of master data across SAP and other business systems.
• Manage compliance with internal audit requirements and regulations.
• Lead efforts to modernize master data processes through automation.

Skills

Data management

SAP proficiency

Data governance

Business intelligence

Education

Bachelor's degree in Computer Science or related field

Tools

SAP

Robotic Process Automation (RPA)

Job description

Permanent

Midrand

Overview

We are a Supply Chain and Sales & Merchandising partner adding value to your business through a fully integrated, temperature‑controlled network in Southern Africa. But we are also more than that. We are people serving people. While we boast the best in tech and infrastructure, our people are our greatest resource. With our skilled, curious, can‑do people at the forefront, our assets become your assets, our service your solutions. Vector’s vehicle fleet includes a food‑industry first in ‘multi‑temperature’ vehicles(Table: food industry first in ‘multi-temperature’ vehicles enabling the company to service business across frozen, chilled and ambient temperature zones on a single delivery).

Job Purpose

To provide vision and expertise on the enterprise information model and data architecture and all corresponding data models throughout the Business in poble of support of enterprise integration, solutions architecture, enterprise reporting and commencer Business Intelligence initiatives, with a clear line of sight towards achieving the business goals.

Key Responsibilities

Operational Management

• Oversee the complete lifecycle of master data (material, customer, vendor, general ledger, pricing) across SAP and other business systems.
• Manage the Business master data model to accurately reflect the organisation’s operational and strategic requirements.
• Facilitate the creation, validation, approval, and maintenance of master data records in collaboration with relevant business functions.
• Coordinate with user functions to ensure completeness, correctness, and consistency of master data requests.
• Manage all data interfaces and mass uploads related to new business take‑on, process changes, and system implementations.
• Monitor and control data redundancy (e.g. duplicate records) using system algorithms and regular manual audits.
• Implement controls to ensure data integrity, accuracy, and alignment across systems through continuous data quality reviews.
• Conduct quarterly data integrity tests and lead initiatives to improve data cleanliness, comprehensiveness, and usability.
• Drive timely communication of changes to master data structures, standards, and processes to all stakeholders.
• Engage with key business stakeholders to align master data with business performance needs and ensure high data integrity.
• Collaborate with IT and business functions to develop and maintain reporting tools that support data quality management and auditing.
• Ensure SLA (Service Level Agreement) compliance and address service issues with appropriate stakeholders.

Data Standards Establishment and Ownership

• Define and document master data standards, including field‑level definitions, business rules, and classification structures.
• Introduce and embed relevant national, international, and Group data standards into master data processes.
• Lead the implementation of master data management systems, covering data definition, maintenance, conversions, and reporting.
• Collaborate cross‑functionally to define and enforce data governance policies, maintenance procedures, and quality controls.
• Deploy workflow solutions that ensure timely, accurate, and compliant creation and approval of master data records.
• Integrate business rules into validation processes at the point of data entry, reducing errors and enforcing consistency.
• Work with IT to build and maintain tools for maintaining master data integrity and alignment across SAP and ancillary systems.
• Establish compliance metrics and controls to continuously monitor and improve data quality.

Reporting

• Develop and deliver monthly management reports and dashboards tracking KPIs related to data quality, accuracy, completeness, and SLA performance.

Innovation & Transformation

• Lead efforts to modernise master data processes by integrating emerging technologies, aligning with broader business and IT strategies.
• Identify, implement, and optimise automation opportunities using tools such as Robotic Process Automation (RPA), SAP automation solutions, and bulk data upload utilities to reduce manual effort and errors.
• Assess current master data workflows to eliminate inefficiencies and redundancies. Design improved processes that enhance data accuracy, processing speed, and responsiveness to business needs.
• Continuously scan the technology landscape for innovations in data management (e.g. AI, Machine Learning, predictive analytics), and evaluate their relevance and application within the organisation.
• Collaborate with IT and data science teams to explore AI‑enabled solutions such as: Duplicate detection and automated cleansing; Intelligent data enrichment and classification; Predictive data suggestions during entry or approval; Natural Language Processing (NLP) to streamline data request submissions.
• Act as a champion for data‑driven decision‑making by_NULL promoting a culture of ownership, data integrity, and continuous improvement across departments.
• Ensure all improvements are proceed scalable and aligned with enterprise architecture principles, enabling consistent standards across all business units and systems.

Governance, Risk and Compliance

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• Ensure master data compliance with internal audit requirements and external regulations such as POPIA and GDPR.
• Establish governance frameworks for master data ownership, stewardship, and accountability across business units.
• Define and manage role‑based access controls for master data in alignment with organisational security policies.
• Participate in internal and external audits, ensuring data practices meet risk and compliance standards.
• Collaborate with internal stakeholders to identify and close compliance gaps in master data processes.
• Support data privacy, retention, and protection policies as they relate to master data.

Technical Expertise

• Act as the subject matter expert (SME) for master data, providing strategic and technical guidance to business and IT leadership.
• Stay current on SAP developments (especially ECC6 and potential S/4HANA migration paths), tools, and integration technologies relevant to master data.

Staff Management

• Lead, coach, and develop a team of master data professionals, ensuring alignment with legislative requirements and company policies.
• Identify and train master data representatives across business functions to support decentralised data maintenance.
• Monitor team performance and provide ongoing feedback, support, and development opportunities.
• Ensure resource availability and adherence to service levels through Gén effective scheduling, time management, and workload allocation.
• Drive succession planning, talent development, and retention initiatives.
• Foster a culture of continuous improvement, accountability, and collaboration through regular team engagement and communication.
• Ensure team compliance with master arall data standards to maintain organisational information fiod financial integrity.
• Promote employment equity and diversity within the team in alignment with organisational targets.

KPI’s

• SLA Achievement: Timely creation and amendment of master data in line with agreed service level agreements (SLAs).
• Master Data Alignment: Accurate reflection of business requirements within master data models and structures.
• Management Engagement: Active and ongoing collaboration with business and functional leadership to ensure data relevance and usability.
• Data Standards Compliance: Adherence to internal data standards and alignment with Group‑wide and external data governance frameworks.
• Data Quality: High levels of accuracy, consistency, and completeness of master data across core systems and integrated platforms.
• Data Synchronisation: Gate keeper and ensures effective integration and alignment ofdoes complement across all interfacing systems.
• Process Automation & Efficiency: Reduction of manual processes through automation, improving turnaround time and reducing error rates.
• Innovation & Continuous Improvement: Delivery of process enhancements, automation solutions, or AI‑driven initiatives to improve master data management.
• Stakeholder Satisfaction: Positive feedback from internal stakeholders on service delivery, responsiveness, and data reliability.
• Team Performance: High Será developed team aligned to master data governance, quality and compliance objectives.

Key Relationships

Internal

• Group managers.
• Planning teams.
• Finance teams.
• Customer Teams.
• Operations Teams.
• IT Teams.
• Corporate support functions.

External

• Customers.
• Principals.