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 United States. You will join a fast‑scaling, data‑driven engineering environment where the accuracy, reliability, and integrity of large‑scale data systems are critical to business success. In this role, you will focus on validating complex ETL/ELT pipelines and ensuring that data flowing across analytics platforms remains consistent, trustworthy, and production‑ready. You will design and implement automation frameworks that strengthen data quality across ingestion, transformation, and downstream consumption layers. Your work will directly impact analytics, reporting, and AI‑driven decision‑making across a rapidly growing SaaS ecosystem. This position requires strong analytical thinking, deep QA automation expertise, and the ability to collaborate closely with data engineering and product teams. You will help shape scalable testing standards and reusable frameworks that improve overall engineering velocity and data reliability. This is a high‑impact role for someone who thrives in complex, data‑intensive environments and enjoys building structured quality systems from the ground up. Accountabilities Design, develop, and maintain automated testing frameworks for ETL/ELT pipelines, data workflows, and analytics systems. Build reusable test components for data platforms such as Snowflake, Databricks, Airflow, ADF, and streaming architectures. Automate schema validation, regression testing, data contract checks, backfill testing, and pipeline monitoring. Create and execute SQL‑based validation scripts to compare source and target datasets and ensure data accuracy. Perform root‑cause analysis of data issues and collaborate with engineering teams to resolve inconsistencies. Develop and maintain test plans, test cases, and regression suites for evolving data products. Partner with data engineers, analysts, and product teams to validate transformation logic and business rules. Participate in Agile ceremonies, including sprint planning, requirement reviews, and release validation. Drive QA best practices and contribute to documentation and reusable automation assets across teams. Requirements 6–10+ years of QA automation experience in data‑intensive or analytics‑focused environments. Strong proficiency in SQL for validation, profiling, and data comparison across systems. Hands‑on experience with Python for automation scripting and data testing workflows. Proven experience testing ETL/ELT pipelines and cloud‑based data platforms. Strong understanding of QA methodologies, test planning, defect lifecycle management, and automation principles. Experience with CI/CD pipelines, Git workflows, and automated testing execution environments. Hands‑on experience with Snowflake and at least one automation or testing framework. Strong analytical and troubleshooting skills for identifying and resolving data quality issues. Familiarity with data orchestration and transformation tools such as Airflow, dbt, or similar platforms (preferred). Exposure to tools such as Great Expectations, Postman, or performance testing frameworks is a plus. Excellent communication skills and ability to collaborate across technical and non‑technical teams. Benefits Competitive annual compensation of 30,000 – 32,000 USD Fully remote work environment with flexible collaboration hours Opportunity to work on large‑scale data systems in a fast‑growing SaaS company Exposure to modern data stack technologies and advanced analytics ecosystems Collaborative, high‑performance engineering culture focused on quality and innovation Professional growth opportunities in data engineering, QA automation, and platform engineering Flexible daily schedule with overlapping US collaboration hours and autonomy outside core time Chance to build impactful automation frameworks used across mission‑critical data pipelines #J-18808-Ljbffr Jobgether