Head of QA Project Management leading a team ensuring products' quality in Innovation projects. Collaborating with stakeholders across R&D, Supply Chain, and Marketing in Denmark.
About the role
- Senior Data Quality Engineer validating data pipelines and ETL processes in LATAM. Collaborating with Data Engineers and Analysts to maintain data quality across systems.
Responsibilities
- Ensure the accuracy, completeness, and consistency of data entering the Data Warehouse
- Validate analytical datasets and data models across warehouse environments
- Analyze datasets to detect data quality issues, inconsistencies, and anomalies
- Perform reconciliation and cross-validation between source systems and warehouse outputs
- Apply data quality standards including completeness, accuracy, consistency, and reliability
- Review and validate ETL pipelines and data integrations feeding the Data Warehouse
- Analyze ingestion workflows and transformation logic across data pipelines
- Validate transformations across staging, processing, and warehouse layers
- Perform source-to-target data validation across environments
- Ensure pipelines deliver high-quality datasets to downstream analytics systems
- Write advanced SQL queries to validate datasets and transformations
- Investigate discrepancies across multiple data sources
- Identify anomalies, unexpected patterns, or data inconsistencies
- Perform root cause analysis on data quality issues across systems
- Develop automated data validation processes using Python
- Implement repeatable validation checks across data pipelines
- Build monitoring checks for data completeness and integrity
- Integrate validation processes into CI/CD pipelines
- Partner with Data Engineers and Data Analysts to maintain reliable analytical datasets
- Support validation activities before data is consumed by analytics platforms or reporting tools
- Collaborate with governance teams to maintain data quality standards
- Document validation rules, processes, and methodologies
Requirements
- 5+ years of experience working with data validation, data quality, or data pipeline reliability
- Proven experience working with Data Warehouses and analytical data models
- Strong experience validating ETL pipelines and data integrations feeding a Data Warehouse
- Experience analyzing large datasets to identify data quality issues, inconsistencies, or anomalies
- Experience supporting data validation processes prior to analytics or reporting consumption
- Experience integrating data validation checks into CI/CD workflows
- Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related technical field.
Benefits
- Professional development opportunities
- Remote work options
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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