QA Automation Engineer (Data)

Jobgether

11h • $30,000 - $32,000 • Remote

About The Position

This role offers an exciting opportunity to ensure data quality and reliability across complex, large-scale data pipelines in a fast-paced, analytics-driven environment. You will design, develop, and maintain automated testing frameworks for ETL/ELT workflows, validate data integrity, and implement monitoring for streaming and batch pipelines. Your contributions will directly impact the accuracy, consistency, and performance of mission-critical data systems. This position combines hands-on automation, SQL-based data validation, and collaboration with cross-functional engineering teams to solve challenging data quality problems. It is ideal for someone passionate about building scalable testing solutions, driving best practices in QA, and working in a remote, flexible, and highly collaborative setting. You will help accelerate the delivery of trustworthy data for analytics and AI initiatives.

Requirements

• 6–10+ years of QA automation experience in data-intensive or analytics-focused environments.
• Strong proficiency in SQL for data validation, profiling, and regression testing.
• Hands-on experience with Python for automation scripting and data quality frameworks.
• Extensive experience testing ETL/ELT pipelines and cloud-based data workflows.
• Familiarity with CI/CD pipelines, version control (Git), and automated execution environments.
• Strong analytical, problem-solving, and troubleshooting skills.
• Excellent written and verbal communication skills.
• Experience with Snowflake and at least one test automation framework; knowledge of Databricks, ADF, AWS Glue, streaming platforms, or orchestration tools is a plus.

Responsibilities

• Design, develop, and maintain automated test frameworks for ETL/ELT and streaming data workflows.
• Build reusable components for Snowflake, Databricks, ADF, Airflow, and other data platforms.
• Automate regression tests, schema validation, data contract checks, and monitoring of data quality.
• Validate data accuracy, completeness, and consistency across ingestion, transformation, and downstream layers.
• Perform root-cause analysis for data inconsistencies and collaborate with engineers to implement corrective actions.
• Participate in Agile ceremonies, review requirements, estimate tasks, and verify deployment outcomes.
• Document QA best practices and create reusable testing assets to elevate overall data quality standards.

Benefits

• Competitive annual compensation: $30,000 – $32,000 USD.
• Remote-first role with flexible working hours and autonomy.
• Opportunity to design and implement scalable data QA frameworks.
• Exposure to modern cloud-based analytics platforms and automation tools.
• Collaborative environment with globally distributed engineering teams.
• Contribution to mission-critical data systems used for analytics and AI innovation.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed