QA Automation Engineer, Data

Job Description:

• Design, develop, and maintain automated test frameworks for data pipelines and ETL workflows.
• Build reusable test components for Snowflake, Databricks, ADF, Airflow, streaming pipelines, and more.
• Automate schema validation, regression testing, backfill testing, and data contract checks.
• Implement automated monitors for stream quality, lag, CDC correctness, and consistency.
• Create, execute, and maintain detailed test cases, test plans, and regression suites for data enhancements.
• Validate data accuracy, completeness, and integrity across ingestion, transformation, and downstream layers.
• Develop SQL-based validation scripts to compare source vs. target datasets.
• Perform root-cause analysis for data inconsistencies and work closely with engineering teams to resolve issues.
• Partner with Data Engineers, Analysts, and Product teams to understand transformation logic and business rules.
• Participate in sprint ceremonies including requirement reviews, estimations, and deployment validations.
• Monitor pipeline execution, identify defects early, and verify fixes through structured retesting.
• Drive QA best practices across multiple data environments.

Requirements:

• 6-10+ years of QA Automation experience in data-intensive or analytics-driven environments.
• Strong proficiency in SQL for data validation, profiling, and regression testing.
• Hands-on experience with Python for automation scripting and data validation.
• Extensive experience testing ETL/ELT pipelines and cloud-based data workflows.
• Deep understanding of QA methodologies, test planning, defect lifecycle management, and automation principles.
• Experience with CI/CD pipelines, Git-based workflows, and automated execution environments.
• Strong analytical and troubleshooting skills for identifying data quality issues.
• Excellent written and verbal communication skills.
• Hands-on experience with Snowflake and at least one test automation framework/tool.

Benefits:

• Remote-first environment with flexibility
• Autonomy
• Strong cross-functional collaboration

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