Senior AQA Engineer
This is usAt 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 jobOur 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.We are seeking a Senior AQA Enginner to join our team and lead testing efforts for our AI-driven products and Enterprise Data Platforms. This is a high-impact role where you will define testing strategies, build automation frameworks, and mentor QA engineers while working closely with cross-functional teams.This is you
7+ years of experience as an AQA Engineer or SDET in complex data-driven environments.
Strong programming and automation skills in Python and SQL.
Expertise in testing Data-Intensive Applications and AI/ML models.
Hands-on experience with databases like Postgres and data warehouses like Snowflake.
Experience with cloud platforms such as AWS, GCP, or Azure.
Proven ability to lead QA efforts and mentor engineers in best practices.
Experience working in cross-functional teams including Data Science, Engineering, and Product.
Familiarity with CI/CD pipelines and test automation tools.
Knowledge of AI fairness, explainability, and model validation techniques.
Experience with Version Control Systems (VCS) like GitHub or GitLab.
Nice-to-have skills:
Hands-on experience with PyTorch, NumPy, and Pandas for data validation.
Experience with Google Gemini and Vertex AI for AI model evaluation.
Familiarity with Looker and LookML for data analytics validation.
Knowledge of CI/CD pipelines and test automation frameworks for ML workflows.
Exposure to AdTech or data-intensive applications.
This is your role
Lead quality assurance efforts for AI/ML-based applications and Enterprise Data platforms.
Design, develop, and maintain automated test frameworks using Python.
Develop and execute comprehensive test plans for ML models, ensuring accuracy, fairness, and robustness.
Validate data pipelines and ETL processes, working with Postgres, Snowflake, and Looker.
Collaborate with Data Engineers, ML Engineers, and Product teams to define quality metrics.
Identify, analyze, and document defects, ensuring timely resolution.
Establish best practices for QA automation, CI/CD pipelines, and test data management.
Mentor and guide junior QA engineers, fostering a culture of quality.
You should be ready to perform not only automation but also manual testing and leadership (however, the focus is on the automation).
Expect the candidate to work in their time zone until noon or 1 PM PT.
We take pride in the diverse skills and character of our teams, welcoming everyone to apply and contribute to our collective strength.
Apply Now
7+ years of experience as an AQA Engineer or SDET in complex data-driven environments.
Strong programming and automation skills in Python and SQL.
Expertise in testing Data-Intensive Applications and AI/ML models.
Hands-on experience with databases like Postgres and data warehouses like Snowflake.
Experience with cloud platforms such as AWS, GCP, or Azure.
Proven ability to lead QA efforts and mentor engineers in best practices.
Experience working in cross-functional teams including Data Science, Engineering, and Product.
Familiarity with CI/CD pipelines and test automation tools.
Knowledge of AI fairness, explainability, and model validation techniques.
Experience with Version Control Systems (VCS) like GitHub or GitLab.
Nice-to-have skills:
Hands-on experience with PyTorch, NumPy, and Pandas for data validation.
Experience with Google Gemini and Vertex AI for AI model evaluation.
Familiarity with Looker and LookML for data analytics validation.
Knowledge of CI/CD pipelines and test automation frameworks for ML workflows.
Exposure to AdTech or data-intensive applications.
This is your role
Lead quality assurance efforts for AI/ML-based applications and Enterprise Data platforms.
Design, develop, and maintain automated test frameworks using Python.
Develop and execute comprehensive test plans for ML models, ensuring accuracy, fairness, and robustness.
Validate data pipelines and ETL processes, working with Postgres, Snowflake, and Looker.
Collaborate with Data Engineers, ML Engineers, and Product teams to define quality metrics.
Identify, analyze, and document defects, ensuring timely resolution.
Establish best practices for QA automation, CI/CD pipelines, and test data management.
Mentor and guide junior QA engineers, fostering a culture of quality.
You should be ready to perform not only automation but also manual testing and leadership (however, the focus is on the automation).
Expect the candidate to work in their time zone until noon or 1 PM PT.
We take pride in the diverse skills and character of our teams, welcoming everyone to apply and contribute to our collective strength.
Apply Now