Verification Engineer -

Position Title: Verification Engineer (Data Products & AI)

Experience Level: 3-5 years of professional experience in quality assurance, testing, or verification engineering

Modes of Work: Hybrid

About the Role

We are seeking a Verification Engineer to ensure the quality, reliability, and performance of our data products and AI-driven solutions. You will design and execute comprehensive testing strategies, validate data pipelines, and verify AI model outputs to ensure they meet business requirements and maintain data integrity.

Key Responsibilities

- Test Strategy & Planning: Develop comprehensive testing plans for data products and AI/ML solutions, including unit, integration, and end-to-end testing
- Data Validation: Verify data accuracy, completeness, and consistency across pipelines using SQL queries and validation frameworks
- AI Model Testing: Evaluate AI/ ML model outputs for accuracy, bias, performance, and reliability
- Test Automation: Design and implement automated test suites for data pipelines and AI predictions using appropriate tools and frameworks
- Azure DevOps Management: Utilize Azure DevOps for test case management, bug tracking, CI/CD pipeline validation, and test execution tracking
- Performance Testing: Conduct performance and load testing on data pipelines and AI inference systems
- Documentation: Create detailed test plans, test cases, and quality reports; maintain comprehensive testing documentation
- Collaboration: Work closely with data engineers, data scientists, and product managers to understand requirements and acceptance criteria
- Continuous Improvement: Identify testing gaps, recommend improvements, and stay updated with emerging testing methodologies for AI/data products
- Production Support: Monitor and troubleshoot issues in production data products and AI systems

Required Qualifications

- 3-5 years of experience in QA/testing, preferably with data products,



data pipelines, or analytics platforms
- SQL Expertise: Advanced SQL skills for data validation, query analysis, and complex data verification
- Data Product Testing: Proven experience testing data warehouses, ETL processes, or analytics solutions
- AI/ML Evaluation: Ability to evaluate and test AI/ML model outputs, including accuracy metrics and result validation
- Azure DevOps: Hands-on experience with Azure DevOps for test management, work item tracking, and CI/CD pipeline validation. Testing ETL/ELT processes, data transformations, and data quality rules
- Testing Methodologies: Robust knowledge of testing best practices (unit, integration, system, regression testing)
- End-to-End AI Pipeline Testing: Verifying complete workflows from data ingestion to model inference and result delivery

Preferred Qualifications (Good to Have)

- Python/Programming: Basic programming knowledge in Python, Java, or similar languages for test automation
- Data Quality Tools: Familiarity with data quality platforms
- Snowflake/Cloud Databases: Experience testing on Snowflake, Azure SQL, or similar cloud data platforms
- AI/ML Concepts: Understanding of machine learning fundamentals, model evaluation metrics, and bias detection
- CI/CD Pipelines: Understanding of continuous integration and continuous deployment practices
- Git & Version Control: Familiarity with Git for test code management
- Agile/Scrum: Experience working in Agile environments

Soft Skills

- Strong communication and documentation abilities
- Ability to collaborate effectively with cross-functional teams (engineers, scientists, product managers)
- Detail-oriented with a mindset for quality excellence
- Proactive problem-solving and critical thinking
- Adaptability and willingness to learn new technologies
- Ownership mentality and commitment to product quality
- Time management and ability to manage multiple testing initiatives Role & responsibilities

Preferred candidate profile

📌 Verification Engineer (Bengaluru)
🏢 Sunovaa Tech
📍 Bengaluru