QA Automation Engineer - Data
New
US, US core collaboration windowsFull-TimeSenior
Salary30,000 - 32,000 USD per year
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Job Details
- Experience
- 6–10+ years
- Required Skills
- PythonSQLApache AirflowETLGitQA AutomationSnowflakeCI/CDDatabricks
Requirements
- 6–10+ years of QA automation experience in data-intensive or analytics-driven environments.
- Strong proficiency in SQL for validation, profiling, and regression testing.
- Hands-on experience with Python for automation scripting and test development.
- Solid experience testing ETL/ELT pipelines and cloud-based data workflows.
- Strong understanding of QA methodologies, defect lifecycle management, and automation frameworks.
- Experience working with CI/CD pipelines, Git-based workflows, and automated test execution systems.
- Familiarity with data platforms such as Snowflake and at least one automation framework.
- Exposure to tools and technologies such as dbt, Kafka, or similar data ecosystems is highly preferred.
- Experience with testing and automation tools such as Selenium, Postman, Apache JMeter, or Robot Framework is a plus.
- Strong communication, collaboration, and problem-solving skills in cross-functional teams.
Responsibilities
- Design, build, and maintain scalable test automation frameworks for data workflows and ETL/ELT pipelines using tools like Apache Airflow, Databricks, and Snowflake.
- Develop reusable validation components for schema checks, regression testing, backfill validation, and data contract enforcement.
- Create and maintain SQL-based and Python-based validation scripts for data accuracy, completeness, and integrity across systems.
- Implement monitoring and testing mechanisms for streaming and batch data pipelines, including latency, CDC correctness, and consistency checks.
- Perform root-cause analysis for data quality issues and collaborate closely with engineering teams to resolve defects.
- Participate in agile ceremonies, including sprint planning, requirement reviews, and deployment validations.
- Drive QA best practices and contribute to the development of documentation and reusable testing assets.
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