Data Quality Engineer

Concentrix is a global technology and services leader that powers the world’s best brands. They are seeking a Data Quality Engineer to define and implement end-to-end testing strategies for a modern data platform built on AWS, ensuring data quality, reliability, and performance across the pipeline.

Responsibilities:

• Define the end-to-end testing scope based on solution architecture and project OPM documentation
• Design and implement a comprehensive testing strategy and plan aligned with organizational QA standards
• Develop and maintain test scripts and frameworks for the Redshift BI Foundations platform
• Perform testing across key technologies, including:
• • AWS Redshift
• • AWS DMS (Data Migration Service)
• • AWS Glue
• • Terraform
• • Python-based data pipelines
• • Apache Airflow (via Astronomer managed interface)
• • dbt (data build tool)
• • Soda.io (data quality and observability)
• Build and implement automated testing solutions to ensure:
• • End-to-end data validation
• • Data ingestion accuracy
• • Transformation logic integrity
• • Data pipeline reliability
• Conduct test coverage analysis and ensure adequate validation across all data engineering workflows
• Prepare and manage test data
• Review and provide feedback on:
• • Solution architecture
• • Data models
• • Design and technical documentation
• Collaborate with cross-functional teams (Data Engineering, BI, DevOps, Product) to:
• • Identify testing impacts
• • Mitigate risks
• • Ensure high-quality deliverables

Requirements:

• Proven experience in data engineering testing / data QA / ETL validation
• Strong hands-on experience with AWS data services (Redshift, Glue, DMS)
• Proficiency in Python for test automation and validation
• Experience with Airflow (Astronomer preferred) and orchestration testing
• Hands-on experience with dbt and data transformation validation
• Familiarity with Terraform for infrastructure validation
• Experience in BI testing in Tableau will be highly beneficial
• Experience with data quality tools such as Soda.io or similar
• Strong understanding of: Data warehousing concepts, ETL/ELT pipelines, Data validation techniques (schema, reconciliation, anomaly detection)
• Experience designing enterprise-level test strategies for data platforms
• Knowledge of CI/CD pipelines for data and test automation
• Experience working in Agile / Scrum environments
• Familiarity with data observability frameworks