QA Automation Engineer - Data

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a QA Automation Engineer - Data in the United States.

This role sits at the intersection of quality engineering, data reliability, and automation excellence within a fast-scaling analytics environment. You will be responsible for ensuring the accuracy, consistency, and trustworthiness of large-scale data pipelines powering mission-critical SaaS products. Working closely with data engineering, analytics, and product teams, you will design and implement robust automated testing frameworks across complex ETL/ELT workflows. The role involves deep validation of data flows across cloud-based platforms and modern data stacks, with a strong focus on scalability and reusability. You will help strengthen data quality practices across the organization while enabling faster, safer delivery of analytics and AI-driven capabilities. This is a high-impact position where your work directly influences the reliability of enterprise data systems.

You will own the design, development, and execution of automated and manual testing strategies for data pipelines and analytics workflows.

• 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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Requirements:

You bring strong experience in data-focused QA automation with deep analytical and technical expertise in modern data ecosystems.

• 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.

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Benefits:

• Competitive annual compensation: $30,000 – $32,000 USD
• Fully remote-first work environment with global collaboration flexibility
• Flexible working hours aligned with US core collaboration windows
• Opportunity to work with modern data platforms and scalable cloud architectures
• High-impact role contributing directly to data integrity and product reliability
• Collaborative, agile environment with strong engineering culture
• Exposure to cutting-edge data engineering, analytics, and automation practices
• Autonomy to design and improve testing frameworks and QA standards