Reliability Quality Integration Engineer

• Based in Hyderabad, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare.
• Be part of an organization driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products.
• Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats.

Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company’s IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy.

A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers.

We are seeking a seasoned Integration QA Lead with 12+ years of experience driving integration, ETL, data migration, and enterprise data quality across complex platforms such as Veeva CRM, Salesforce, middleware, and connected upstream/downstream systems. This role requires strong expertise in SIT, end-to-end and regression testing, SQL-based validation, XRAY test governance, defect management, and cross-system reconciliation, combined with practical AI literacy using tools such as Copilot, Gemini, and others to improve testing efficiency, quality insights, and delivery predictability. The successful candidate will champion integration reliability, data integrity, traceability, and quality engineering excellence across large-scale transformation programs.

• →Own end-to-end quality assurance for integrations, ETL processes, data migrations, APIs, middleware, and cross-platform data flows.
• →Define integration and data testing strategies, test plans, coverage models, quality gates, validation approaches, and release readiness criteria.
• →Lead integration testing, ETL testing, data migration validation, SIT, End-to-End testing, regression testing, and reconciliation activities across multiple enterprise systems.
• →Validate source-to-target mappings, transformation logic, business rules, and data quality requirements to ensure complete and accurate data movement.
• →Drive test design, execution, traceability, and reporting through JIRA XRAY, ensuring linkage between requirements, test cases, defects, and releases.
• →Perform and govern SQL based validation activities to verify data integrity, completeness, accuracy, and consistency across systems.
• →Manage the end-to-end defect lifecycle, including defect triage, root cause analysis, prioritization, risk assessment, and closure governance.
• →Collaborate with Product Owners, Business Analysts, Data Engineers, Architects, Application Teams, and Integration Teams to embed quality throughout the SDLC.
• →Coordinate test data preparation, environment readiness, dependency management, mock services, and execution planning across multiple workstreams.
• →Establish data reconciliation frameworks, reporting mechanisms, and validation processes to support large-scale data migrations and integrations.
• →Monitor and report QA KPIs, defect trends, migration quality metrics, integration risks, and overall testing status to leadership stakeholders.
• →Leverage AI tools such as Copilot, Gemini, and ChatGPT to accelerate test design, data validation, defect analysis, documentation, impact assessments, and reporting.
• →Drive continuous improvement initiatives and AI-enabled testing innovations to enhance testing efficiency, coverage, and quality outcomes.
• →Mentor QA engineers and integration testers, fostering a culture of quality ownership, accountability, collaboration, and continuous learning.
• →Support release governance by providing quality assessments, migration readiness evaluations, integration risk analysis, and go/no-go recommendations.
• →Partner with vendor and offshore teams to ensure adherence to testing standards, governance processes, and quality commitments.
• →Ensure compliance with organizational QA processes, documentation standards, audit requirements, and data governance practices.

Required

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 12+ years of experience in Integration Testing, ETL Testing, Data Migration Validation, or Enterprise Quality Assurance.
• Strong experience with enterprise platforms such as Salesforce CRM, Veeva CRM, Veeva Vault CRM, middleware solutions, APIs, and related integrations.
• Hands-on expertise in SQL based data validation, reconciliation, and data quality verification.
• Experience validating ETL processes, data transformations, source-to-target mappings, and large-scale migration activities.
• Strong expertise with JIRA XRAY, test management, defect governance, and quality reporting.
• Experience with API and integration testing tools and methodologies.
• Hands-on AI literacy through the use of available tools such as Copilot, Gemini, ChatGPT, and similar technologies.
• Knowledge of Agile, Scrum, Waterfall, SDLC, and STLC methodologies.
• Excellent analytical, stakeholder management, problem-solving, and communication skills.

Preferred

• Experience in Life Sciences, Healthcare, or other regulated industries.
• Experience supporting large-scale CRM transformation programs, enterprise data migrations, and multi-market deployments.
• Knowledge of Informatica, Data Bricks, MuleSoft, or similar integration and ETL platforms.
• Experience with data warehousing, data governance, master data management, and data quality frameworks.
• Exposure to automation frameworks using Python, Robot Framework, or comparable technologies.
• Experience applying AI-enabled quality engineering practices, advanced analytics, and agentic AI concepts to testing and validation activities.
• Familiarity with cloud-native integration architectures and enterprise data ecosystems.

Current Employees apply HERE

Current Contingent Workers apply HERE