Quality Engineering Lead (Test Lead)

Posted:
10/4/2024, 5:04:13 AM

Location(s):
Tamil Nadu, India ⋅ Noida, Uttar Pradesh, India ⋅ Chennai, Tamil Nadu, India ⋅ Uttar Pradesh, India

Experience Level(s):
Expert or higher ⋅ Senior

Field(s):
AI & Machine Learning ⋅ Data & Analytics

Project Role : Quality Engineering Lead (Test Lead)
Project Role Description : Leads a team of quality engineers through multi-disciplinary team planning and ecosystem integration to accelerate delivery and drive quality across the application lifecycle. Applies business and functional knowledge to develop end-to-end testing strategies through the use of quality processes and methodologies. Applies testing methodologies, principles and processes to define and implement key metrics to manage and assess the testing process including test execution and defect resolution.
Must have skills : IBM Sterling Commerce
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: As a Quality Engineering Lead (Test Lead), you will lead a team of quality engineers to accelerate delivery and drive quality across the application lifecycle. You will apply business and functional knowledge to develop end-to-end testing strategies and implement key metrics to manage and assess the testing process. Roles & Responsibilities: - Expected to be an SME, collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Provide solutions to problems for their immediate team and across multiple teams. - Lead a team of quality engineers through multi-disciplinary team planning and ecosystem integration. - Apply business and functional knowledge to develop end-to-end testing strategies. - Implement key metrics to manage and assess the testing process. - Define and implement test execution and defect resolution processes. Professional & Technical Skills: - Must To Have Skills: Proficiency in IBM Sterling Commerce. - Strong understanding of statistical analysis and machine learning algorithms. - Experience with data visualization tools such as Tableau or Power BI. - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information: - The candidate should have a minimum of 7.5 years of experience in IBM Sterling Commerce. - This position is based at our Chennai office. - A 15 years full time education is required.

15 years full time education

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with 750,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. We are uniquely able to deliver tangible outcomes because of our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song. These capabilities, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com

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Accenture

Website: https://accenture.com/

Headquarter Location: Dublin, Dublin, Ireland

Employee Count: 10001+

Year Founded: 1989

IPO Status: Public

Last Funding Type: Grant

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