Senior Manager Quality Engineering

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As a Sr. Mgr. of Engineering Automation Quality, you will operate at both a strategic and execution level defining automation vision, establishing governance standards, modernizing testing frameworks, and building high-performing quality engineering teams. Serve as a subject matter expert in quality engineering practices across multiplatform applications and determine strategic direction under the guidance of systems leadership. You will lead the full quality engineering lifecycle, including automation strategy, test architecture design, implementation, performance validation, release quality governance, and continuous improvement of software systems and applications. You will drive quality transformation across application, API, UI, cloud-native, and enterprise data platforms while ensuring scalability, security, reliability, and operational excellence. The ideal candidate combines strong people leadership with deep technical expertise in automation, cloud platforms, data engineering validation, and secure technology solutions that support critical business operations
What You Will Do
Quality Engineering - Strategy, Transformation and AI-Enabled Innovation

• Define and execute the workstream automation and quality engineering roadmap aligned with technology and business strategy
• Establish governance frameworks, standards, and KPIs for automation, performance testing, and data quality validation
• Drive modernization of legacy testing practices toward scalable, automation-first and DevOps-aligned delivery models
• Lead shift-left quality initiatives and continuous testing strategies across the software development lifecycle
• Drive adoption and responsible implementation of agentic AI tools to enhance quality engineering productivity and intelligence such as
• Automated test case generation and optimization
• Intelligent regression test selection
• Root cause analysis and defect pattern identification
• Automated code review insights and quality risk detection
• Establish governance, security, and compliance standards for AI-assisted development and testing workflows
• Promote human-in-the-loop validation models to ensure reliability, explainability, and accountability in AI-driven quality decisions
  

Automation & Technical Oversight

• Oversee automation across:
• API testing (Karate + Maven or similar frameworks)
• UI automation (Selenium with Java or Python, JUnit, TestNG)
• Data pipelines and warehouse platforms
• Ensure strong automation coverage for large-scale data engineering workflows and ETL validation
• Establish best practices for validating data accuracy, transformation logic, reconciliation, and integrity

• Lead quality initiatives across AWS-based architectures,
• including services such as Glue, EMR, Lambda, S3, and CloudWatch
• Ensure seamless integration of automation frameworks into CI/CD pipelines using Jenkins, GitLab, or similar tools
• Oversee performance, resiliency, scalability, and reliability testing across distributed systems
  

Risk Management & Operational Excellence

• Implement defect prevention frameworks, root cause analysis practices, and release governance models
• Ensure compliance with security, regulatory, and enterprise risk standards
• Monitor cost optimization and resource efficiency within quality engineering operations
• Define measurable quality metrics to continuously improve delivery outcomes
  

Organizational & Team Leadership

• Build, scale, and mentor high-performing automation and quality engineering teams
• Develop leadership bench strength and technical capability within the organization
• Provide performance leadership through clear objectives, career development planning, mentoring, and active coaching of automation engineers and quality leaders
• Own team performance and overall success of assigned initiatives, ensuring on-time, high-quality delivery
• Influence workforce planning, and team capability development
• Foster a culture of accountability, engineering excellence, and continuous improvement
• Influence cross-functional stakeholders including Architecture, Product Owners, Engineering, Infrastructure, and Data leadership
• Champion continuous improvement initiatives that elevate engineering maturity, automation efficiency, and overall organizational capability
  

What You Will Bring

• Bachelor s degree in Computer Science or Information Systems or equivalent experience

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  Minimum eight (8) to ten (10) years experience in systems including at least two (2) years experience directly leading people, including developing, motivating, and directing people
• Excellent understanding of software quality engineering principles, methodologies, and industry best practices
• Strong background in test automation frameworks (e.g., Selenium, Playwright, RestAssured, JUnit/TestNG, Cucumber, Python, etc.), experience in mentoring the test automation teams preferred.
• Experience integrating automation into CI/CD pipelines (Jenkins, GitLab, GitHub Actions, Azure DevOps, etc.)
• Experience balancing automation investment with ROI, cost efficiency, and long-term maintainability
• Strong data-driven mindset with the ability to translate automation investments into measurable business value
• Solid understanding of cloud platforms (AWS/Azure/GCP), Particularly, AWS tech stack like Glue, etc.,
• Experience or familiarity validating enterprise data warehouse environments and large-scale ETL/data engineering workflows
• Experience in testing orchestration, excellent analytical, problem-solving and debugging skills, with an excellent ability to troubleshoot and resolve complex design and issues.
• Excellent communication skills with the ability to influence senior stakeholders and engineering leadership team
• Strong ability to manage cost optimization, tooling strategy, and resource allocation within quality engineering functions
• Familiarity with AI-assisted engineering or intelligent automation tools preferred
• Demonstrated ownership mindset with strong collaboration and stakeholder management skills
  

What Will Set You Apart

• Proven experience leading enterprise-wide automation transformation initiatives that significantly improved test coverage, release velocity, and defect reduction
• Demonstrated ability to deliver measurable productivity gains through automation frameworks and AI-enabled quality engineering tools
• Experience implementing agentic or AI-assisted testing solutions such as intelligent test generation, self-healing automation, regression optimization, or automated root cause analysis
• Strong executive communication skills with the ability to translate quality metrics into business impact, risk mitigation, and financial outcomes
• Experience defining and governing enterprise quality KPIs including defect escape rate, deployment frequency, MTTR, automation ROI, and test cycle efficiency
• Track record of building and scaling high-performing quality engineering organizations, including mentoring leaders and establishing communities of practice
• Deep understanding of quality practices in cloud-native and distributed systems environments, including data engineering and enterprise data warehouse validation
• Experience establishing release governance frameworks, risk-based testing models, and defect prevention strategies in complex or regulated environments
• Demonstrated ability to align automation investments with cost optimization, operational scalability, and long-term maintainability
• Experience influencing architectural decisions to embed quality early in the software development lifecycle
  

We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age, race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.