Senior MDM Validation Engineer - INTL LATAM

Required Skills & Experience

• 5+ years of Data Engineering, Data Quality, or Data Validation experience
• SQL
• Snowflake
• DBT
• MDM concepts and processes
• GitHub
• CI/CD
• Kafka
• Data Validation
• Data Quality Testing
• Source-to-Target Mapping
• Kimball Methodology
• Jira
• Confluence

Nice to Have Skills & Experience

• AI-generated code validation
• Master Data Management (MDM)
• Data governance frameworks
• Medallion Architecture (Raw, Silver, Gold Layers)
• Data warehouse modernization initiatives
• Hospitality, gaming, or customer analytics environments

Job Description

We are seeking a Senior MDM Data Validation Engineer to support enterprise data management initiatives focused on master data quality, governance, and integration. This role will be responsible for testing and validating data pipelines, MDM processes, and AI-assisted development outputs while ensuring the accuracy, consistency, and reliability of enterprise data assets.

Responsibilities

• Validate MDM data pipelines and master data processing workflows.
• Execute testing activities for customer, marketing, gaming, and enterprise data domains.
• Review and certify AI-generated DBT code supporting MDM processes.
• Perform data quality assessments, reconciliation activities, and defect analysis.
• Validate Kafka-based data ingestion and transformation workflows.
• Ensure Kimball methodology principles are applied appropriately within analytical data models.
• Support deployment validation through GitHub repositories and CI/CD pipelines.
• Partner with architects and business stakeholders to define testing requirements and success criteria.
• Identify data quality issues and collaborate with engineering teams through resolution.
• Create and maintain validation documentation within Confluence.
• Track defects, testing activities, and delivery milestones using Jira.
• Support data governance and master data standardization initiatives.