Master Data Management Specialist

Main Responsibilities:

Cleaning Customer / Commercial Data

• Support customer master data validation including reviews of large datasets across Europe and other regions.
• Develop an understanding of the depth of dataset errors detecting anomalies outliers and trends using cross-checking against reliable external sources. Examples could include; names addresses registration numbers etc.
• Data Validation and Duplication Identification: Use company supplied tools to validate data accuracy and duplicate records.
• Data Enrichment: Enhancing existing data by filling in missing details from reliable external sources.
• Leveraging AI to identify errors automatically if possible.
• Working within current company data governance policies.
• Scaling techniques to tackle large datasets and suggest improvements.
• Reporting to colleagues and leadership on a routine basis for final validation before datasets are sent to support teams for ERP inputs.
• Apply critical judgment to determine appropriate methods for handling incomplete conflicting or ambiguous data
• Collaborate with cross-functional teams to clarify data definitions and resolve conflicting information
• Document findings decisions and data transformation processes clearly and thoroughly
• Assess the downstream impact of data changes before implementing corrections
• Identify patterns and trends within messy datasets to distinguish meaningful insights from noise

Other Responsibilities

• At all times work in a way that demonstrates Veolia Water Tech business methods and ethics.
• To listen to and relay any relevant market intelligence.
• Maintain high standards in terms of personal appearance conduct and respect of Company property.

Qualifications :

Degree in business or equivalent business experience.

Fluent English required

Additional Information :

As an inclusive company Veolia is committed to diversity and gives equal consideration to all applications without discrimination.

Remote Work :

Yes

Employment Type :

Full-time