Data Quality & Test Engineer

Role : Data Quality & Test Engineer Experience: 5 - 8 Years Location: Hybrid / Remote Employment: Full-time Role & Responsibilities: - Perform data validation and quality testing for data pipelines, ETL/ELT, ML workflows, and cloud infrastructure. - Validate raw, curated, and summarized data layers, including schemas, mappings, transformations, and business rules. - Perform end-to-end source-to-target reconciliation. - Develop and execute unit, integration, regression, data quality, and automation tests for AWS Glue, Lambda, Step Functions, and APIs. - Validate CI/CD deployments and releases. - Monitor logs, CloudWatch metrics, dashboards, and alerts. - Validate IAM, RBAC, data access controls, and security configurations. - Document test results, defects, quality metrics, and testing activities. Required Skills: - 5 - 8 years of experience in Data Testing, ETL Testing, Data Quality, or QA Automation. - Strong experience with Data Warehouse, Data Lake, or modern data platforms. - Hands-on experience with AWS Glue, Lambda, Step Functions, S3, CloudWatch, and IAM. - Strong SQL skills for complex data validation and reconciliation. - Experience with Python and test automation, preferably PyTest. - Experience with REST API testing and event-driven architectures. - Experience with CI/CD tools such as Azure DevOps, GitHub Actions, Jenkins, or GitLab CI/CD. - Knowledge of unit, integration, regression, UAT, defect management, and data quality testing. - Understanding of IAM/RBAC, security, and observability. Preferred: - Lakehouse and ML workflow testing. - Great Expectations / PyTest. - Terraform / CloudFormation. - AWS certifications.