Senior Payroll Specialist

About the Role

As a Senior Payroll Specialist on the Global Payroll team, you'll lead biweekly payroll processing for all U.S. salaried and hourly employees. The Global Payroll team manages end-to-end payroll operations across five continents, partnering with HR, Finance, Accounting, and Legal to deliver accurate, compliant, and scalable payroll services. You'll own the full U.S. payroll cycle, including equity-related payroll, and serve as the go-to resource for resolving employee payroll inquiries with speed and precision.

What you'll do:

• Own end-to-end biweekly U.S. payroll processing for salaried and hourly employees, including daily payroll cycles for non-qualified stock options.
• Execute payroll input compilation from multiple sources, validating data for accuracy and completeness before each cycle.
• Drive timely resolution of employee payroll inquiries in Jira within SLA, performing root cause analysis to prevent recurrence.
• Partner with HR, Finance, and cross-functional teams to process employee changes in payroll and cross-check data accuracy.
• Lead timecard tracking and reconciliation to ensure alignment between timekeeping systems and payroll records.
• Support continuous process improvements by identifying opportunities for automation and efficiency gains in payroll workflows.

Required Skills and Experience:

• Experience with multi-state payroll processing experience, with demonstrated expertise in federal, state, and local tax compliance.
• Proven experience processing payroll for employee populations that receive equity compensation, including restricted stock units.
• Hands-on proficiency with payroll platforms (e.g., UKG Pro, Workday HCM) and HRIS integrations in a high-volume environment.
• Track record of resolving complex payroll issues independently, with documented root cause analysis and process improvement outcomes.
• Proficiency in Google Workspace, Slack, Atlassian tools (Jira), and Apple products for daily collaboration and case management.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
• Fluency with cloud-native data environments (e.g., Snowflake, Databricks, BigQuery) and their metadata, lineage, and governance capabilities at scale.