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.