We are seeking a Senior Data Quality Engineer to ensure the reliability, accuracy and integrity of data across modern data platforms and analytics solutions. The specialist will be responsible for designing and implementing data quality verification processes, validating ETL pipelines and supporting testing activities across cloud-based data ecosystems.
Responsibilities
- Design and implement data quality verification processes for data products and analytics solutions
- Perform data migration testing and validate data consistency across systems
- Collaborate with product, engineering and customer teams to define testing strategies and quality requirements
- Implement and execute testing for ETL and data ingestion pipelines
- Perform Databricks testing using Notebooks and Python scripting
- Validate BI reports, dashboards and data visualization outputs
- Develop automated data validation and quality control processes using Python
- Support CI/CD processes for data pipelines and data quality workflows
- Analyze and troubleshoot data discrepancies, inconsistencies and performance issues
- Establish and improve data quality processes and governance practices from scratch
Requirements
- 4+ years of experience in Data Quality verification, Data Governance or Data Visualization testing
- Strong understanding of data ingestion pipelines and data storage concepts, including OLTP databases and Data Warehousing
- Advanced SQL skills
- Experience with at least one cloud platform such as AWS, Azure or GCP
- Hands-on experience with ETL testing
- Knowledge of CI/CD principles and best practices in data processing
- Experience with Python for data validation and test automation
- Strong analytical and problem-solving skills
- Excellent interpersonal and communication abilities
- Ability to build and establish data quality processes from scratch
- Upper-Intermediate English language proficiency (B2)
Nice to have
- Experience with Databricks testing and notebook automation
- Knowledge of modern BI and analytics platforms
- Experience with automated testing frameworks for data pipelines
- Understanding of Data Governance best practices
- Familiarity with large-scale cloud-based data platforms