[Hiring] Sr QA Automation Engineer @Nybble Group

Role Description

The Data QA Automation Engineer is responsible for designing and implementing data-focused quality solutions for an innovative platform within the veterinary sector. The platform integrates and standardizes clinical data from multiple management systems, enabling advanced capabilities such as automated medical condition prediction using Machine Learning and LLM technologies, as well as automated insurance claim processing. This role specializes in creating high-quality test datasets, validating complex data transformations, and ensuring the reliability of AI-driven workflows.

The engineer will work with large, complex clinical datasets, transforming restricted and unstructured data formats into structured validation assets used for model evaluation and automated testing. As part of an AI-first engineering team, this role leverages AI-assisted development tools to accelerate data preparation, automation workflows, and testing processes while maintaining strong standards for data integrity and reliability.

Responsibilities

• Design, build, and maintain automated pipelines to generate, transform, validate, and clean large test datasets.
• Create high-fidelity test data sets to support backend validation, Machine Learning workflows, and AI model evaluation.
• Transform complex and restricted clinical data formats into structured test payloads and validation scenarios.
• Develop automated test suites to evaluate data pipelines, model outputs, and AI-driven feature performance.
• Define repeatable testing processes to measure model accuracy, consistency, and reliability.
• Collaborate with Data Scientists, AI Engineers, Backend Engineers, and Product Managers to establish validation criteria and quality standards.
• Perform data validation, ETL testing, and backend testing across complex data flows.
• Identify data quality issues, inconsistencies, and gaps that may impact AI/ML workflows.
• Leverage AI-assisted development tools such as Claude to accelerate script creation, data generation, parsing routines, and automation coverage.
• Improve testing frameworks and processes to increase engineering velocity and reduce feedback cycles.
• Take ownership of data quality initiatives and independently drive solutions in a fast-paced environment.

Qualifications

• Strong experience as a QA Automation Engineer with a focus on data validation, ETL testing, or backend testing.
• Advanced scripting experience with Python or similar languages for data manipulation and automation.
• Experience working with large, complex, structured, and unstructured datasets.
• Strong understanding of data quality, data integrity, and validation strategies.
• Experience working with relational databases, particularly PostgreSQL.
• Familiarity with Graph Databases such as Neo4j and/or Vector Databases such as Pinecone is highly desirable.
• Experience building automated testing frameworks and repeatable validation processes.
• Hands-on experience using AI-assisted development tools and LLM workflows to improve testing efficiency.
• Strong analytical mindset with attention to data accuracy, reproducibility, and evaluation metrics.
• Ability to independently identify data issues, design solutions, and implement improvements.
• Ability to work effectively under tight deadlines in a fast-paced engineering environment.
• Advanced English level with strong communication skills for remote collaboration across technical teams.

Nice to Have

• Experience testing AI/ML models and data science pipelines.
• Familiarity with Machine Learning evaluation techniques and model validation approaches.
• Experience working with healthcare, veterinary, insurance, or other regulated data environments.
• Knowledge of cloud data platforms and modern data architectures.
• Experience with CI/CD pipelines and automated quality gates.
• Familiarity with AI agents, LLM evaluation frameworks, or AI-powered QA practices.
• Strong interest in AI-first engineering methodologies and data-driven quality practices.

Benefits

• Competitive compensation and benefits package.
• Opportunities for growth and professional development.
• Comprehensive leave policies, including PTO, sick leave, and study leave.
• Access to employee discount programs.
• Monthly connectivity allowance.