Mphasis is hiring a Senior QA Engineer for its Noida Sector 142 location. This is an exciting opportunity for QA professionals who want to move beyond conventional web testing and build expertise in AI platforms, data quality, API testing, automation and modern data engineering environments such as Snowflake.
📍 Location: Mphasis, Noida Sector 142
💼 Role: Senior QA Engineer
🎯 Experience: 2–4 Years
👥 Openings: 1
🆔 Job ID: 113826-35-1
🧪 Focus: AI & Data Platform QA, API Testing, Data Quality, Automation
🏢 About Mphasis
Mphasis is an AI-led, platform-driven technology company that helps global enterprises modernize, adopt AI and scale their technology environments. The company has a strong presence across industries including banking and financial services, insurance, healthcare, retail, logistics and travel. Mphasis states that it has 31,000+ employees across 21 countries and continues to invest heavily in AI-powered platforms and enterprise transformation.
Its Mphasis.ai business and platforms such as NeoIP™ focus on embedding AI and intelligent automation across enterprise technology and processes. This makes the current QA opening particularly relevant for testers interested in the rapidly growing intersection of software quality, AI and data engineering.
🌟 Why This Role Is Good for Your Experience
This position offers considerably broader exposure than a traditional functional QA role. You will be testing AI and data platforms, validating data accuracy and completeness, testing REST/SOAP APIs and implementing automation strategies.
The data-quality component is especially valuable. You can develop experience in source-to-target validation, reconciliation, duplicate detection, transformation validation and pipeline testing—skills that can open doors to Data QA, ETL Testing, Data Engineering QA and Quality Engineering roles.
The preferred Snowflake exposure adds another valuable skill to your profile. Combined with Python/JavaScript, API automation, CI/CD and performance testing, the role can help you build a modern SDET + Data QA profile.
🧠 Skills Required
- Data Quality Testing: Accuracy, completeness, consistency, uniqueness, validity and reconciliation
- AI Platform Testing: Model outputs, data pipelines, AI workflows and edge cases
- API Testing: REST/SOAP, HTTP methods, authentication, JSON/XML and negative testing
- Automation: Selenium/Playwright or equivalent frameworks and reusable automation design
- Programming: Python or JavaScript for test automation and data validation
- Snowflake: SQL queries, joins, aggregations and warehouse validation
- Database Testing: Source-to-target comparison and data integrity checks
- CI/CD: Git, Jenkins/GitHub Actions/Azure DevOps concepts
- Performance Testing: JMeter, LoadRunner, k6 or similar tools
- Testing Fundamentals: SDLC, STLC, Agile, regression, integration and defect lifecycle
- Tools: Jira/test-management platforms and defect-tracking systems
🎯 Expected Mphasis Interview Rounds
Round 1 – HR/Recruiter Screening: Expect questions about your experience, current project, notice period, location, compensation and relevant QA skills.
Round 2 – Technical QA Round: Prepare for testing fundamentals, test scenarios, defect management, automation framework concepts, API testing and project-based questions.
Round 3 – Data & Automation Deep Dive: For this JD, expect strong focus on SQL, data validation, ETL/data quality, API testing, automation and possibly Snowflake. Recent Mphasis interview reports include SQL, ETL testing, DWH, Selenium, automation frameworks and scenario-based questions.
Round 4 – Coding/Problem Solving: Recent Mphasis QA Automation interview feedback mentions technical questions followed by two coding questions, so prepare basic-to-intermediate programming problems.
Round 5 – Managerial/Client/HR: Be ready for project ownership, Agile collaboration, communication, stakeholder management and scenario-based quality decisions.
💰 Salary Range
Public Mphasis salary data shows Quality Engineer compensation varying significantly by experience; AmbitionBox reports approximately ₹5.9–7.6 LPA for 4 years and ₹7.1–9.1 LPA for 5 years for Quality Engineers.
For this specialized 2–4 year Senior QA Engineer position involving AI/data platforms, API automation and data quality, a reasonable market expectation is approximately ₹7–12 LPA. This is an indicative estimate, not an official Mphasis salary range, and the actual offer may depend on technical expertise, project requirements and level mapping.
🔥 Preparation Tips
- Master SQL: Practice joins, subqueries, CTEs, window functions, aggregations and duplicate detection.
- Practice data reconciliation: Given source and target datasets, identify missing, mismatched and duplicate records.
- Learn Snowflake basics: Understand warehouses, schemas, tables, stages and querying large datasets.
- Prepare API scenarios: Test authentication, invalid payloads, boundary values, response schemas, latency and error handling.
- Create an API automation project: Use Python/Java with REST Assured, Requests or Pytest and integrate it into CI.
- Understand AI QA: Learn how to validate model outputs, detect inconsistent results, test edge cases and measure accuracy.
- Prepare ETL questions: Know source-to-target mapping, transformation validation and end-to-end pipeline testing.
- Practice coding: Focus on strings, arrays, collections, file/data processing and SQL-based problems.
📄 Resume Tips
Avoid presenting yourself simply as a “QA Tester.” Position yourself as an Automation + Data Quality + API Testing Engineer.
Put these keywords prominently in your resume: AI Testing, Data Quality Testing, API Automation, REST/SOAP, SQL, Snowflake, Automation Framework, Python/JavaScript, CI/CD, ETL Testing and Agile.
Use measurable achievements such as:
- “Automated API regression suite covering 200+ REST endpoints, reducing regression effort by 60%.”
- “Performed source-to-target data validation across 1M+ records and identified critical transformation defects.”
- “Developed SQL-based data-quality checks for accuracy, completeness and duplicate detection.”
If you have AI experience, clearly mention model validation, AI output testing, data-pipeline testing or LLM evaluation instead of simply writing “AI testing.”
📩 How to Apply
👉 Application Link: Click Here
🤝 Referral Tip
Want to improve your chances of getting noticed?
Connect with someone at Mphasis and request a referral—it can significantly enhance your visibility in the hiring process.
Interested candidates should apply through the official Mphasis Careers portal and search for Job ID 113826-35-1 – Senior QA Engineer, Noida. Mphasis officially directs candidates to create a profile and apply through its career’s portal.
🚀 Final Takeaway
The Mphasis Senior QA Engineer opportunity is a strong choice for professionals who want to combine traditional QA with AI, data and automation engineering. The biggest differentiator will be your ability to demonstrate practical expertise in SQL/data validation + API testing + automation + AI/data-platform testing.
If you can confidently explain how you would validate a data pipeline from source to API to database, automate critical scenarios, investigate data mismatches and assess AI-generated outputs, you will be much better positioned for this role. 🚀
