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# QA Automation Engineer-Data/Backend Testing

- **Company:** HAN IT STAFFING, INC.
- **Location:** Hanover, NJ, United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Automation of Tests, Big Data, Cloud Computing, Continuous Integration, Data Validation, Information Engineering, Data Integrity, Extract Transform Load (ETL), Data Transformation, Database Queries, Database Testing, Github, Python (Programming Language), Log Analysis, Scrum Methodology, Regression Testing, Cloud Services, Selenium, Test Data, Scripting, Postman, Apache Spark, Backend, Pytest, Data Lakes, Gitlab-ci, Apache Kafka, Restful APIs, Data Pipelines, Jenkins, Databricks
- **Published:** October 29, 2026
- **Apply:** https://www.thejobnetwork.com/job/22b9e079-58f5-40f0-af7a-3687014ec59a/qa-automation-engineerdatabackend-testing

## About the Role

* Strong experience in QA Automation and Backend/Data Testing.
 * Proficiency in Python for automation scripting.
 * Experience with Apache Spark and ETL/data pipeline testing.
 * Hands-on experience with AWS services (S3, Glue, Lambda, EMR, Redshift, Athena, or similar).
 * Experience with automation tools such as PyTest, Selenium, Robot Framework, or similar.
 * Strong SQL skills for data validation and database testing.
 * Experience testing REST APIs using Postman, Rest Assured, or similar.
 * Familiarity with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI., * Experience with cloud-native data platforms and data lakes.
 * Knowledge of Airflow, Kafka, or Databricks.
 * Understanding of Agile/Scrum methodologies.
 * Excellent analytical, troubleshooting, and communication skills.

## Description

* We are looking for a hands-on QA Automation Engineer with strong experience in backend and data testing. The ideal candidate should have a solid understanding of data engineering concepts, automation frameworks, and cloud technologies. This role involves validating data pipelines, ETL processes, APIs, and backend systems while ensuring data quality and reliability., * Develop and execute automated test cases for backend applications, APIs, and data pipelines.
 * Validate ETL processes, data transformations, and large-scale datasets.
 * Perform data quality, data integrity, and regression testing.
 * Build and maintain automation frameworks using Python.
 * Test data processing workflows built on Spark and AWS services.
 * Collaborate with Data Engineers and Developers to identify and resolve defects.
 * Analyze logs, troubleshoot issues, and support CI/CD testing processes.