QA Engineer - Payroll

Distro; Dadri; On-site; INR 500,000 - 900,000; Full time

Job summary

Distro is seeking a meticulous QA professional with strong knowledge of U.S. payroll, benefits, and compliance. This role supports payroll, compliance, and benefits areas with working hours overlapping U.S. time zones.

You will define data requirements for payroll scenarios, conduct regression testing, and collaborate across teams to ensure high-quality payroll software solutions for clients.

Qualifications

• Keen eye for spotting discrepancies in payroll data and tax calculations.
• Strong understanding of U.S. payroll and taxes.

Responsibilities

• Define and stage data requirements for payroll scenarios, including deductions and tax rates.
• Conduct regression testing using manual and automated tools to ensure stability.
• Create, maintain, and update test cases based on changes.
• Review and validate U.S. payroll calculations in various scenarios.
• Participate in the full SDLC within an Agile environment.
• Apply QA best practices and use QA tools effectively.
• Track, report, and mitigate application issues and risks.
• Collaborate with automation QA to prioritize test automation improvements.

Skills

Keen Eye for Detail

Solid Understanding of U.S. payroll

Education

College degree or equivalent (Computer Science preferred)

Tools

Excel

Job description

We are looking for a meticulous, quality driven QA professional with extensive understanding of U.S. payroll, benefits and compliance issues.

This is an exciting opportunity to contribute to a quality-driven team that takes pride in delivering high-impact payroll software solutions to our clients. This role will work within our payroll, compliance and benefits areas with working hours that overlap with U.S. hours.

Job Responsibilities

• Define, establish, and stage data requirements for different payroll scenarios and calculations. This includes testing different employee demographics, wage structures, types of deductions, tax rates and brackets involving multiple jobs and locations.
• Conduct regression testing to ensure stability and quality of the product. This includes a combination of manual testing and automated testing tools.
• Create, maintain, and update test cases based on the changes/modifications implemented by the team.
• Review and validate U.S payroll calculations in different scenarios.
• Participate in the entire development life cycle from concept to release in an Agile environment.
• Understand and participate in software industry standard quality assurance practices, including but not limited to test case design, software defect reporting, and Agile testing techniques, as well as common software QA tools.
• Analyzes, tracks, and re****ports on application issues.
• Regularly summarizes testing status and areas of risk, and wherever possible propose and execute mitigation strategies.
• Employs a sound risk management approach to determine well-structured and comprehensive test strategies for assigned projects.
• Collaborate with automation QA engineers to identify and prioritize areas for significant efficiency and confidence gains through test automation.

Required Skills

• Keen Eye for Detail: Ability to spot discrepancies, inconsistencies and errors in payroll data and tax calculations with a high degree of accuracy.
• Solid Understanding of U.S. payroll and taxes

Qualifications

• 2+ years of experience within the PEO industry, coupled with significant hands-on experience with software applications commonly used within the PEO industry.
• Education: College degree or equivalent experience, preferably in Computer Science
• Analytical Thinking: Ability to interpret and apply tax rules, analyze payroll data, and troubleshoot complex issues.
• Technical Proficiency: Comfortable working with Excel and/or other tools used for data analysis.
• Time Management: Ability to prioritize tasks and manage time effectively in a demanding environment.
• Communication Skills: Ability to communicate effectively in a clear and concise manner. Ability to document and explain findings across other disciplines with the team and leadership.
• Organization: Ability to organize large bodies of work and structure in logical way

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