Key Purpose:

The Master Data Analyst ’s purpose is to manage and maintain critical data, ensuring its accuracy, consistency, and timeliness across various systems. They focus on developing and maintaining master data systems, implementing data governance policies, and using data to extract key business insights, which is critical for key decision-making

Key Duties & Responsibilities    
Key Outputs and Accountabilities include, but not limited to:

Accurate and Consistent Master Data

• Ensure customer, outlet, route, pricing, and product data is accurate, complete, and maintained consistently across all platforms (e.g., SFA, ERP, CRM).
• Maintain data integrity by conducting regular audits and reconciliation processes.

Timely Data Maintenance

• Support quick turnaround times for new customer creation, updates to existing records, route changes, and pricing modifications.
• Enable rapid onboarding of new accounts and territories without disruption to sales execution.

Support for Sales Execution and Route to Market

• Provide clean, updated customer and route data that enables the SFA system to function effectively for sales reps.
• Ensure territory and route structures in the system reflect real-world sales team organization and distribution models.

Compliance with Data Governance Policies

• Enforce and align with internal data standards and governance policies.
• Maintain audit trails and adhere to regulatory or business rules around data handling (e.g., GDPR, customer segmentation).

Effective Issue Resolution and User Support

• Act as the point of contact for data-related issues from the sales, customer service, and distribution teams.
• Collaborate with IT, commercial, and digital teams to resolve data discrepancies and system issues.

Enable Reporting and Analytics

• Ensure data is structured to support commercial reporting, territory planning, and performance analytics.
• Collaborate with BI teams to improve data visibility and insights for decision-making.

Process Improvement and Automation

• Identify opportunities to streamline master data workflows using automation tools or system enhancements in collaboration with the Group Office Master Data team
• Contribute to projects aimed at improving data flow between systems (e.g., SFA ? ERP).

Stakeholder Collaboration

• Work closely with Sales, Marketing, Distribution, IT, and Finance teams to ensure data meets cross-functional needs.
• Address any discrepancies or issues within master data which can affect the effectiveness of the RTM strategies.
• Participate in cross-departmental initiatives impacting customer data or sales tools

Skills, Experience & Education    
Education

• Bachelor’s degree in Information Systems, Computer Science, Business Administration, Data Management, or a related field

Experience

• 4–5 years experience managing customer/product/route/pricing master data, ideally in FMCG, CPG, or bottling environments
• Hands-on experience with SFA platforms (e.g., Salesforce), understanding their role in field execution
• Exposure to working with sales, marketing, supply chain, and finance teams

Skills

Technical Skills

• Proficiency in Excel (advanced level: formulas, pivot tables, lookups)
• Experience with data tools like SQL, Power BI, Tableau (optional but valuable) including proficiency in maintaining large datasets, ensuring accuracy and consistency for reporting and analysis
• Familiarity with data workflow tools or ticketing systems (e.g., ServiceNow, Jira)
• Understanding of data integration (ETL concepts, APIs)

 Analytical & Process Skills

• Strong attention to detail and data accuracy
• Process-oriented mindset with ability to map and improve workflows
• Analytical thinking to spot data trends and resolve anomalies

Soft Skills

• Strong communication and interpersonal skills (written and verbal)
• Customer-centric mindset—responsive and solution-focused
• Ability to collaborate across functions and with field teams
• Organizational and time management skills (handling multiple requests with SLAs)

Behavioral Competencies

• Proactive problem-solving
• Accountability and ownership of data quality
• Adaptability in a fast-changing, digital environment
• Confidentiality and integrity with sensitive commercial data