Offer summary

Qualifications:

3+ years of experience as a QA Engineer or SDET., Strong programming and automation skills in Python and SQL., Experience with high-volume data processing systems and data pipelines., Familiarity with cloud platforms like AWS, GCP, or Azure..

Key responsibilities:

Develop and execute test plans for data pipelines and ETL processes.

Build and maintain test automation frameworks using Python and SQL.

Validate data integrity and performance across large datasets.

Collaborate with cross-functional teams to identify and resolve defects.

Job description

This is us

At Qinshift and Avenga we are merging together to start a new era of technology that matter. Leveraging the power of innovations, we are on a journey to shape the future of work, and we are inviting you to co-create it with us.

This is the job

Our client is a leading tech company specializing in data-driven solutions for digital advertising and AI analytics. They provide scalable, high-performance data platforms for real-time decision-making, leveraging AI and machine learning to optimize marketing strategies.

They seek an experienced Automation QA Engineer to test high-volume data processing systems, ensure AI-driven solution reliability, and enhance automation frameworks.

The role focuses on automation but also requires some manual testing, specializing in Data/AI/ML.

This is you

3+ years of experience as a QA Engineer or SDET.
Strong programming and automation skills in Python and SQL.
Experience testing High-Volume Data Processing Systems and data pipelines.
Hands-on experience with databases like Postgres and data warehouses like Snowflake.
Familiarity with cloud platforms such as AWS, GCP, or Azure.
Experience with Version Control Systems (VCS) like GitHub or GitLab.
Strong problem-solving skills and attention to detail.

Nice-to-have skills:

Experience with data validation frameworks and testing data transformations.
Familiarity with CI/CD pipelines and test automation tools.
Exposure to AdTech or other data-intensive applications.

This is your role

Develop and execute test plans for data pipelines, ETL processes, and Enterprise Data Platforms.
Build and maintain test automation frameworks using Python and SQL.
Validate data integrity, transformations, and performance across large datasets.
Perform functional, integration, and performance testing for data warehouses and databases.
Identify, analyze, and document defects, working closely with Data Engineers to resolve issues.
Ensure CI/CD pipeline integration for automated data testing.

Collaborate with cross-functional teams, including Data Engineering and Product teams

Required profile