Data QA Architect or Test architect

Role Overview: As the QA Architect, Data Products, you will be a senior individual contributor and technical lead responsible for owning the quality of data products end-to-end. You will play a key role in shaping the testing strategy across application and AI products in collaboration with the QA Manager. Your role will require a unique combination of skills including product intuition, data engineering literacy, AI-native fluency, and hands-on automation depth. Additionally, you will have the opportunity to mentor a small team of QA engineers, guiding them in technical aspects. Key Responsibilities: - Designing test strategies and ensuring coverage and quality of test strategy artifacts across data, application, and AI products. - Implementing synthetic data capability to cover customer configuration variations, ensure HIPAA compliance, and drive team adoption. - Ensuring data product quality by reducing data incidents, schema breaks, and pipeline defects reaching downstream consumers or customers. - Providing automation coverage and reliability at system and component layers for the products you oversee. - Driving AI tooling adoption within the team and measuring the usage of AI-assisted workflows. - Mentoring QA engineers to facilitate their skill growth, measured through delivery quality and career progression. Qualifications Required: - 710 years of experience in software quality engineering with a clear progression into technical leadership or architecture. - Background in product testing, including validating business behavior, partnering with product managers, and understanding customer experiences. - Hands-on experience in testing data pipelines, ETL/ELT workflows, data APIs, or reporting products. - Experience in designing test data strategies, using synthetic data generation, and understanding HIPAA and PII constraints. - Proficiency in testing highly configurable platforms with varying customer setups. - Strong hands-on automation skills at system and component levels using languages like Python, Java, TypeScript, Playwright, Pytest, TestNG, etc. - Active usage of AI tools in testing practices, including generating test cases, producing synthetic data, and utilizing LLMs. - Exposure to evaluating AI or ML model outputs, including evaluation harnesses, prompt regression, drift or bias detection. - Bachelors degree in Computer Science, Engineering, Information Systems, or equivalent practical experience. Note: The additional details section of the company was not specified in the provided job description. Role Overview: As the QA Architect, Data Products, you will be a senior individual contributor and technical lead responsible for owning the quality of data products end-to-end. You will play a key role in shaping the testing strategy across application and AI products in collaboration with the QA Manager. Your role will require a unique combination of skills including product intuition, data engineering literacy, AI-native fluency, and hands-on automation depth. Additionally, you will have the opportunity to mentor a small team of QA engineers, guiding them in technical aspects. Key Responsibilities: - Designing test strategies and ensuring coverage and quality of test strategy artifacts across data, application, and AI products. - Implementing synthetic data capability to cover customer configuration variations, ensure HIPAA compliance, and drive team adoption. - Ensuring data product quality by reducing data incidents, schema breaks, and pipeline defects reaching downstream consumers or customers. - Providing automation coverage and reliability at system and component layers for the products you oversee. - Driving AI tooling adoption within the team and measuring the usage of AI-assisted workflows. - Mentoring QA engineers to facilitate their skill growth, measured through delivery quality and career progression. Qualifications Required: - 710 years of experience in software quality engineering with a clear progression into technical leadership or architecture. - Background in product testing, including validating business behavior, partnering with product managers, and understanding customer experiences. - Hands-on experience in testing data pipelines, ETL/ELT workflows, data APIs, or reporting products. - Experience in designing test data strategies, using synthetic data generation, and understanding HIPAA and PII constraints. - Proficiency in testing highly configurable platforms with varying customer setups. - Strong hands-on automation skills at system and component levels using languages like Python, Java, TypeScript, Playwright, Pytest, TestNG, etc. - Active usage of AI tools in testing practices, including generating test cases, producing synthetic data, and utilizing LLMs. - Exposure to evaluating AI or ML model outputs, including evaluation harnesses, prompt regression, drift or bias detection. - Bachelors degree in Computer Science, Engineering, Information Systems, or equ