CI Master Data Associate

Your Role

The CI Master Data Manager CI & RGM is responsible for the hands-on preparation and maintenance of commercial intelligence data used across market, category, segment, brand, channel, customer, competitor, KPI and forecasting activities. The role ensures data from approved internal and external sources is collected, cleaned, standardised, validated and stored so that downstream analytics and reporting teams can access consistent and reliable information.

Working with Commercial Intelligence and RGM teams, markets, Data and Technology teams, platform owners and third-party providers, the role supports source mapping, data onboarding, quality controls, issue resolution, dashboard inputs and documentation across HIVE, Databricks, MSS, Power BI and related environments. This is a hands-on individual-contributor role and does not require people leadership.

In this Role you will play Key role in

Key Accountabilities

1. Data Requirements and Source Mapping

• Identify and document internal and external data sources aligned to commercial intelligence use cases and KPI needs.
• Assess source relevance, coverage, quality and gaps across markets, categories and channels.
• Maintain mapped repositories of approved local and central data inputs, ownership, refresh frequency and downstream usage.

2. Data Collection, Cleansing and Standardisation

• Collect raw category, segment, brand, channel, trade, customer, competitor, KPI and forecasting data from approved sources.
• Clean data to resolve errors, duplicates, missing values and inconsistencies, and apply standard formats and transformation rules.
• Harmonise core dimensions including SKU, category, brand, segment, channel, customer, format and geography.
• Maintain validated datasets, input logs and structured files using standard templates.

3. Data Validation and Quality Controls

• Run systematic quality checks, reconciliations and feedback loops to validate accuracy, completeness, consistency and reliability.
• Validate data changes, enhancements and new inputs following defined testing and approval requirements.
• Document quality issues, evidence, corrective actions and resolution status.
• Escalate material or recurring defects to accountable data, technology or provider teams.

Key Accountabilities

1. Data Requirements and Source Mapping

• Identify and document internal and external data sources aligned to commercial intelligence use cases and KPI needs.
• Assess source relevance, coverage, quality and gaps across markets, categories and channels.
• Maintain mapped repositories of approved local and central data inputs, ownership, refresh frequency and downstream usage.

2. Data Collection, Cleansing and Standardisation

• Collect raw category, segment, brand, channel, trade, customer, competitor, KPI and forecasting data from approved sources.
• Clean data to resolve errors, duplicates, missing values and inconsistencies, and apply standard formats and transformation rules.
• Harmonise core dimensions including SKU, category, brand, segment, channel, customer, format and geography.
• Maintain validated datasets, input logs and structured files using standard templates.

3. Data Validation and Quality Controls

• Run systematic quality checks, reconciliations and feedback loops to validate accuracy, completeness, consistency and reliability.
• Validate data changes, enhancements and new inputs following defined testing and approval requirements.
• Document quality issues, evidence, corrective actions and resolution status.
• Escalate material or recurring defects to accountable data, technology or provider teams.

Your Profile

• 3-4 years of hands-on experience in master data, commercial data operations, data quality, business intelligence or analytics support.
• Practical experience collecting, cleansing, standardising, validating and consolidating multi-source commercial data.
• Working knowledge of data repositories, data models, metadata, mapping tables, KPI reporting and issue-management processes.
• Strong Excel capability; working exposure to Power BI, HIVE, Databricks, SQL or comparable data and reporting platforms preferred.