Quality Assurance Manager

Role: 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 Test Strategy & Leadership 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