Quality Assurance Manager

Kanerika Inc; Hyderabad; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Kanerika Inc is seeking an experienced QA Manager to lead the QA function within the Product Development team in Hyderabad. You will own end-to-end test strategy across data engineering, BI/analytics, and AI/ML lines, mentor QA engineers, and drive a quality-first culture with stakeholders to define acceptance criteria and robust automation.

You will build scalable testing frameworks, ensure release quality, and collaborate closely with Dev, PM, and clients to deliver reliable, accurate, and

Qualifications

• 8–12 years of QA/testing experience with 3+ years in a leadership role.
• Experience scaling QA processes for enterprise data products.
• Strong manual and automated testing methodologies across functional, regression, and performance testing.
• Experience with test management and defect tracking tools (JIRA, Zephyr, TestRail).
• Proven release quality sign-off and QA timeline management.

Responsibilities

• Define and own the overall QA strategy across data, BI, and AI/ML product lines.
• Lead testing across multiple concurrent projects and manage timelines.
• Build, mentor, and grow a team of QA engineers and analysts.
• Establish QA processes, defect management, and test documentation standards.
• Coordinate UAT with client stakeholders and sign off on release readiness.

Skills

QA Leadership

Automation & SQL

Soft Skills

Education

Bachelor's or Master's degree

ISTQB certification

Tools

Selenium

Playwright

Cypress

Postman

REST Assured

Job description

We are looking for an experienced QA Manager to lead the Quality Assurance function within Kanerika's Product Development team. You will own the end-to-end test strategy across our data engineering, BI/analytics, and AI-ML product lines, build and mentor a team of QA engineers, and drive a quality-first culture across the organization. You will work closely with Development Managers, Product Managers, and client stakeholders to define acceptance criteria, establish robust automation frameworks, and ensure every release meets Kanerika's standards for reliability, accuracy, and performance.

Key Responsibilities

• Define and own the overall QA strategy across Kanerika's data, BI, and AI/ML product lines
• Build robust, scalable testing frameworks that align with core engineering and business objectives
• Lead testing efforts across multiple concurrent projects, balancing priorities and deadlines
• Define quality benchmarks, acceptance criteria, and go/no-go release standards

Team Management

• Manage, mentor, and grow a team of QA engineers and analysts
• Conduct performance reviews, set goals, and support career development within the team
• Plan hiring and resourcing for QA needs across active and upcoming projects
• Review team output for consistency, thoroughness, and quality of documentation

Automation & Test Frameworks

• Architect and drive adoption of test automation frameworks across web, API, and data layers
• Evaluate and select automation tooling (e.g., Selenium, Playwright, Cypress, Postman, REST Assured)
• Integrate automated test suites into CI/CD pipelines for continuous quality feedback
• Champion reusable, maintainable test assets to reduce regression testing effort over time

Data & AI Quality Assurance

• Define QA approaches specific to data pipelines, ETL processes, and BI/analytics dashboards
• Validate data accuracy, completeness, and consistency across source and target systems
• Establish testing protocols for AI/ML model outputs, including accuracy, bias, and performance checks
• Partner with data engineering and data science teams to catch quality issues early in the pipeline

Process, Governance & Reporting

• Establish and maintain QA processes, defect management workflows, and test case documentation standards
• Run sprint-level quality gates in partnership with Agile/Scrum delivery teams
• Own UAT coordination with client stakeholders and sign-off on release readiness
• Report on quality metrics, defect trends, and test coverage to engineering and client leadership
• Identify recurring risk areas and drive root-cause fixes rather than one-off patches

Required Skills & Qualifications

Primary Skill: QA Leadership & Test Management (Mandatory)

• 8–12 years of overall QA/testing experience, including 3+ years in a QA management or lead role — this is a non-negotiable requirement
• Proven experience building and scaling QA processes for enterprise software or data products
• Strong command of manual and automated testing methodologies across functional, regression, and performance testing
• Experience with test management and defect tracking tools (JIRA, Zephyr, TestRail, or equivalent)
• Track record of owning release quality sign-off and managing QA timelines under delivery pressure

Secondary Skill: Automation & SQL (Required)

• Hands-on experience with automation frameworks such as Selenium, Playwright, or Cypress
• API testing experience using Postman, REST Assured, or similar tools
• Strong SQL proficiency for validating data accuracy across pipelines, warehouses, and BI outputs
• Familiarity with CI/CD tools (Azure DevOps, Jenkins, or equivalent) for integrated test automation
• Understanding of Agile/Scrum delivery and how QA integrates into sprint cycles

Soft Skills

• Strong leadership and team management skills
• Excellent written and verbal communication, able to translate technical quality issues for non-technical stakeholders
• Quality-first mindset with meticulous attention to detail
• Self-driven, process-oriented, and comfortable working under delivery pressure
• Collaborative team player who thrives in a cross-functional, fast-paced environment

Education & Certifications

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field
• ISTQB certification (or equivalent QA certification) preferred
• Certifications in test automation tools or cloud platforms (AWS, Azure, GCP) are a plus

Nice to Have

• Prior experience testing BI/reporting platforms such as Power BI or Cognos
• Exposure to AI/ML model validation or data governance frameworks
• Working knowledge of Python for test automation and data validation scripting
• Experience testing products in a client-facing, multi-project consulting environment