5 - 10 years

15 - 30 Lacs

Posted:4 days ago| Platform: Naukri logo

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Work Mode

Remote

Job Type

Full Time

Job Description

Purpose

The Quality Engineer (QE) will play a key role in establishing a scalable, automation-driven QA framework across Data Intelligence initiatives. This role focuses on improving data quality, automation test efficiency, and release confidence for Azure-based platforms, including Databricks, Power BI, and Azure Functions. The QE will enable a shift-left testing approach, integrating QA early into the development lifecycle to ensure data integrity, system reliability, and continuous delivery alignment within a cloud-first environment. This is a hands-on engineering role for an experienced QE with deep data testing expertise, strong automation skills, and proven experience integrating QA into CI/CD pipelines. The resource will partner with Data Engineering, Analytics, and Development teams to deliver measurable improvements in quality, automation coverage, and defect prevention.

Key Deliverables

End-to-End Test Coverage:

Data Validation & Quality Assurance:

• CI/CD Integration:

QA Process Standardization:

Jira-Based QA Management:

AI-Augmented Testing:

• Reporting & Visibility:

Performance & Resilience Testing:

Required Skills & Experience

• Strong knowledge of test automation and data validation.

• Expertise in Selenium, Postman, GitHub, and GitHub Actions for CI/CD testing automation.

• Hands-on experience testing in Azure environments, including Databricks, Azure Functions, and Power BI.

• Strong SQL proficiency for data analysis, test data management, and validation.

• Experience executing tests across Agile/Scrum delivery models.

• Familiarity with AI tools for QA, Jira, Confluence, SharePoint, and Git-based repositories.

Preferred Qualifications

• Proven experience building or optimizing CI/CD pipelines for automated testing.

• Background in data governance, masking, and compliance (PHI, PII).

• Experience with performance/load testing tools such as JMeter or BlazeMeter.

• Exposure to AI/ML or data science model validation. Soft Skills & Attributes

• Strong analytical, documentation, and communication skills.

• Detail-oriented and highly organized with an automation-first mindset. • Proactive, self-driven, and capable of operating independently in a fast-paced environment.

• Committed to continuous improvement and measurable quality outcomes.

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