Business Information & Analytics Manager (JHB North) at Aspen Pharma Group

OBJECTIVE OF ROLE

• The Data & Analytics Manager is responsible for establishing, governing, and evolving Aspen SA Commercial’s data and analytics capability. The role ensures that trusted, high-quality, well-governed data is available to enable operational excellence, commercial insight, regulatory compliance, and informed decision-making across the business.
• The role is accountable for the design and operation of modern data platforms, including cloud-based technologies such as Microsoft Fabric, and for enabling advanced analytics by ensuring high-quality, well[1]governed, and trusted data foundations across the organisations. The role will be required to explore and implement AI-driven improvements to the existing methodologies and frameworks and to ensure that strict governance is adhered to in the use of these tools

KEY RESPONSIBILITIES

• Lead, coach, develop and manage Data and Analytics team across all analytics platforms to deliver innovative, accurate and on time solutions for SA Commercial.
• Directs and oversees technical teams in the translation of business requirements and functional specifications into logical program designs.
• Partner with BRMs, business leaders, and BEX to prioritise data initiatives.
• Support cross-functional teams such as salesforce Effectiveness, Sales, Marketing, Supply Chain, HR, and Finance, on day-to-day execution of projects.
• Identify and translate business needs into data capability requirements.
• Act as a SME and trusted advisor on data[1]driven decision making.
• Ensure that training and support is available for all users.
• Business lead on the data acquisition, management, and deployment for SA Commercial.
• Own and manage Aspen SA Commercial’s data platforms and pipelines and ensure data accuracy.
• Ensure reliable ingestion of data from SAP and other enterprise systems.
• Design scalable, secure, and future-ready data architectures.
• Oversee the development of automated, scalable, and thoroughly documented reporting solutions – Future Ready Architecture.
• Work closely with IT to provide appropriate data and tools for the analytics team to be successful.
• Enable AI-driven analytics and advanced insight generation by ensuring data is structured, governed, and fit for machine learning and automation use cases.
• Partner with business, BEX, and Group teams to support responsible and scalable AI adoption.
• Establish and enforce data quality standards Implement data governance practices including ownership, definitions, and controls.
• Ensure compliance with internal policies and regulatory requirements.
• Own and develop the vision, strategy, and execution for data analytics, ensuring scalability of systems, processes, and talent across SA Commercial.
• Explore and propose new tools, methodology and practices enabling standardisation of procedures and their related reports.
• Manage external business partners to ensure that service levels are met, invoicing processes completed, contract negotiations, renewals and terminations are completed in compliance to legal requirements.
• Ensure that the BI environment is stable and sales performance and operational reports are available to business timely.
• Drive innovation by developing a future-ready data-driven culture

Requirements
EDUCATIONAL REQUIREMENTS

• Matric (Grade 12)
• Bachelor’s degree in computer science, Data Informatics, Information Systems, Information Technology or any other related degree
• Preferred: Postgraduate in Computer Science, Data Informatics, Information Technology or related

KNOWLEDGE & EXPERIENCE REQUIREMENTS

• 5+ years’ experience leading data and analytics teams
• 8+ years’ experience in BI/Data/Analytics
• Data Warehouse design and Implementation
• Data processing and process modelling
• Implementation of Data Governance Frameworks
• Experience with MS Fabric and other data related technology
• Experience with Enterprise Data Platforms (Azure Cloud, SAP)
• Experience in managing teams and partners
• Exposure to regulated industries is preferred (such as Pharma, FMCG, Banking)
• Experience delivering multiple projects with diverse stakeholders

SOFT SKILLS AND COMPETENCY REQUIREMENTS

• Strong analytical and systems thinking
• Ability to translate business needs into data solutions
• Pragmatic leader who balances speed with quality
• Comfortable operating across business and technical domains
• Excellent stakeholder management and communication skills – with ability to communicate with both business and technical teams
• Structured, disciplined, and delivery-oriented
• High levels of accountability and ownership
• Strong analytical, reasoning, and problem-solving skills
• Excellent planning, Organising and coordinating skills
• Strong leadership skills and ability to use resources efficiently
• Ability to work under pressure
• Ability to think strategically and innovatively
• Risk management
• Results driven, accountable
• Effective Problem-solving and decision-making
• Commercial and strategic awareness
• Strong interpersonal skills and Influencing capabilities

COMPUTER SKILLS REQUIRED

• Data engineering and integration (ETL/ELT, APIs)
• Data modelling (analytical and operational models)
• Data quality, master data management, and reconciliation
• Cloud data platforms (Azure, Fabric, Data Lake concepts)
• SAP data structures and integration patterns
• BI and analytics enablement
• Data governance, security, and access controls
• Understanding of GxP data considerations (advantageous)
• Commercial value chain and related processes
• Pharmaceutical business, business models and stakeholders, including FMCG and Finance
• Data Analytics tools, concepts, architecture
• Business and Data platforms e.g., Fabric/SQL//Excel/SAP
• Data integration
• IT Service Management
• Agile Project Management
• Planning, Budgeting and Forecasting processes Partner/vendor/SLA
• Contract management, negotiation, and renewal
• Microsoft Fabric (OneLake, data engineering, semantic models, analytics enablement)
• Cloud data platforms and modern data architecture
• Integration of AI and advanced analytics capabilities within enterprise data platforms
• Understanding of AI-driven analytics use cases and data requirements