Test QA Automation Engineer – Data & Analytics
Join our remote team as a Test QA Automation Engineer focused exclusively on Data & Analytics. This is a pivotal mid-level role where you will design and implement robust automation frameworks to ensure the accuracy and reliability of our critical data pipelines and platforms.
Key Responsibilities
Design, develop, and maintain automated QA frameworks for Data & Analytics platforms.
Implement automation strategies for data ingestion, transformations, ETL/ELT workflows, and data warehouse validation.
Build scalable, reusable frameworks for end-to-end data validation.
Develop and maintain DBT tests for schema validation, data quality, referential integrity, and business rule validation.
Validate transformed datasets for accuracy, completeness, and consistency.
Perform ETL/ELT testing across multiple enterprise data sources.
Validate source-to-target mappings, reconciliation, and transformation logic.
Automate regression, smoke, reconciliation, and deployment validation testing.
Integrate testing frameworks with Apache Airflow and CI/CD pipelines.
Collaborate closely with Data Engineers, BI Engineers, and Analytics teams.
Implement automated controls for anomaly detection, duplicate checks, and governance requirements.
Required Skills & Experience
Strong, dedicated experience in Data & Analytics QA Automation (not traditional Application QA).
Hands-on experience with DBT test automation and data validation frameworks.
Solid understanding of Data Engineering concepts and ETL/ELT processes.
Advanced SQL skills for complex data validation and analysis.
Experience with Apache Airflow or similar orchestration tools.
Exposure to cloud-based data platforms, with AWS preferred.
Proven ability to test enterprise-scale data pipelines and analytics platforms.
Strong knowledge of Data Warehousing and Dimensional Modeling.
Excellent troubleshooting and analytical problem-solving skills.
Nice-to-Haves
Experience with Databricks, Snowflake, Redshift, or similar modern data platforms.
Familiarity with CI/CD and DevOps practices for Data Platforms.
Experience with Automated Data Reconciliation and Monitoring tools.
Experience supporting BI and Analytics reporting environments.