QA Engineer

Gazelle Global; Polska; On-site; PLN 330,000 - 428,000; Full time

Job summary

Gazelle Global is seeking a QA Engineer to strengthen our data-intensive applications. The role combines test automation, API/backend testing, data validation, and ETL testing within an Agile/Scrum environment.

You will design and maintain automated test suites for APIs and data pipelines, conduct manual and regression testing, validate ETL processes and data quality, and collaborate with developers and data engineers to improve testing coverage and quality across environments.

Qualifications

• Strong knowledge of SQL and database testing.
• Proficient in Python for test automation.
• Experience with API and backend testing.
• Experience with ETL testing and data validation.

Responsibilities

• Design, develop, and maintain automated test suites for APIs, backend services, and data pipelines.
• Perform manual, functional, regression, integration, and release testing.
• Validate ETL processes, data transformations, data quality, and database outputs.
• Create and execute test cases based on business and technical requirements.
• Support release activities and deployment validation across environments.
• Analyze test results, investigate defects, and collaborate with developers to identify and resolve issues.
• Contribute to the improvement of QA processes, automation coverage, and testing frameworks.
• Work closely with cross-functional teams to identify quality risks throughout the software development lifecycle.

Skills

SQL

Python

Microsoft Azure

API testing

Data validation

ETL testing

Agile/Scrum

QA best practices

Tools

Azure Data Factory

Databricks

GitLab

CI/CD pipelines

Job description

We are looking for a QA Engineer to join our team and contribute to the quality and reliability of data-intensive applications. The role combines test automation, API/backend testing, data validation, and ETL testing, working closely with developers and data engineers in an Agile/Scrum environment.

The ideal candidate is technically strong, analytical, and proactive, with a focus on improving test coverage and overall software quality.

Key Responsibilities

• Design, develop, and maintain automated test suites for APIs, backend services, and data pipelines.
• Perform manual, functional, regression, integration, and release testing.
• Validate ETL processes, data transformations, data quality, and database outputs.
• Create and execute test cases based on business and technical requirements.
• Support release activities and deployment validation across environments.
• Analyze test results, investigate defects, and collaborate with developers to identify and resolve issues.
• Contribute to the improvement of QA processes, automation coverage, and testing frameworks.
• Work closely with cross-functional teams to identify quality risks throughout the software development lifecycle.

Required Skills

Must Have

• Strong knowledge of SQL and database testing.
• Good programming skills in Python, particularly for test automation.
• Experience working with Microsoft Azure.
• Hands-on experience with API and backend testing.
• Experience with ETL testing, data validation, and data transformation.
• Experience with Azure Data Factory, Databricks, or similar data integration tools.
• Understanding of Agile/Scrum methodologies.
• Good knowledge of software testing principles and QA best practices.

Nice to Have

• Experience with GitLab and CI/CD pipelines.
• Experience with Treasure Data.
• Experience testing cloud-based or data-intensive applications.
• Familiarity with automated testing of data pipelines and distributed data processing environments.

Preferred Profile

• Previous experience in QA Automation, preferably within data-intensive or backend-focused environments.
• Strong analytical and problem-solving skills with excellent attention to detail.
• Ability to understand complex data flows, APIs, databases, and ETL processes.
• Comfortable working in cross-functional Agile teams.
• Proactive approach to identifying quality risks and improving testing practices.
• A continuous improvement mindset, with a strong focus on software quality and automation.