QA Engineer – Data Validation & Automation (AI-Enabled)

Company: Blumetra Solutions

Job Function: Digital Assurance / Quality Engineering

Location: Hyderabad, Telangana, India (Hybrid)

Experience: 1–3 Years

Employment Type: Full-time

Job Summary Blumetra Solutions is looking for a motivated and detail-oriented QA Engineer with 1–3 years of experience in data validation, SQL testing, ETL/ELT testing, API testing, and functional testing.

The candidate will be responsible for validating data pipelines, integrations, data models, analytics solutions, and applications while developing and maintaining automated test scripts and reusable validation utilities.

Hands-on knowledge of SQL, Python, API testing, and AI-assisted development tools such as Claude is desirable. Exposure to Snowflake, Databricks, AWS, or Azure will be an added advantage.

The ideal candidate should have strong analytical skills, attention to detail, a learning mindset, and the ability to translate business requirements into effective test scenarios and data quality checks.

Key Responsibilities

• Data Validation & Testing
• Validate data pipelines, ETL/ELT processes, data integrations, and data transformations.
• Perform source-to-target data validation to ensure accuracy, completeness, consistency, and integrity.
• Identify missing records, duplicate data, data mismatches, and transformation issues.
• Support testing of data models, dashboards, reports, and visualizations.
• SQL Testing
• Write and execute SQL queries for data validation and reconciliation.
• Use joins, subqueries, aggregate functions, and filtering conditions to validate data.
• Verify business rules, transformation logic, record counts, and data quality.
• Investigate data discrepancies and report findings to the development team.
• Functional, API & Integration Testing
• Execute functional testing based on business requirements and acceptance criteria.
• Perform API testing to validate responses, status codes, payloads, and error handling.
• Support end-to-end and system integration testing across applications and data platforms.
• Prepare test scenarios and test cases for new features and enhancements.
• Test Automation & AI-Assisted Development
• Develop and maintain basic automated test scripts using Python and relevant testing frameworks.
• Use Playwright or comparable tools for application and end-to-end test automation, as applicable.
• Use Claude or other AI-assisted development tools to create, enhance, and troubleshoot test scripts and reusable QA utilities.
• Validate AI-generated code and test outputs before using them in testing activities.
• Support the maintenance and version control of automation scripts.
• Cloud & Data Platform Testing
• Support testing of data pipelines and integrations involving Snowflake, Databricks, AWS, or Microsoft Azure.
• Develop an understanding of data warehouse concepts, data models, and Medallion Architecture (Bronze, Silver, and Gold layers).
• Validate data movement across systems and architectural layers.
• Test Documentation & Defect Management
• Prepare and maintain test cases, test data, test execution reports, and defect logs.
• Document test results and maintain requirements traceability where applicable.
• Identify, report, track, and retest defects using Jira or similar tools.
• Support root-cause analysis and collaborate with developers and data engineers to resolve issues.
• Use AI tools to improve test documentation and reporting efficiency.
• Agile Delivery & Collaboration
• Participate in sprint planning, daily stand-ups, sprint reviews, and retrospectives.
• Work closely with QA leads, developers, data engineers, business analysts, and project teams.
• Understand user stories, acceptance criteria, dependencies, and expected business outcomes.
• Follow established QA processes, checklists, and quality standards.
• Take ownership of assigned testing activities and ensure timely closure of open issues.

Required Skills & Experience

• 1–3 years of experience in QA testing, data testing, database testing, or quality engineering.
• Strong SQL fundamentals and practical experience validating data.
• Understanding of ETL/ELT testing, data integration, and source-to-target validation.
• Knowledge of functional testing, test case design, defect reporting, and regression testing.
• Basic hands-on experience with API testing tools such as Postman or equivalent.
• Exposure to Python scripting or…