SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Drata is seeking a Total Rewards Analyst to strengthen the accuracy, scalability, and insightfulness of compensation programs while providing operational support across benefits and total rewards. This role combines compensation analysis with AI enablement to modernize workflows.
Key responsibilities include analyzing internal and external compensation data to support salary ranges, job leveling, compa-ratio analysis, and pay equity reviews. You will support the planning and execution of annual merit, bonus, and equity review cycles—including modeling, budgeting, manager guidance, system preparation, testing, communications, and post-cycle audits. You'll prepare analyses and recommendations for new hires, promotions, transfers, and off-cycle adjustments, while maintaining accurate job, level, range, and compensation data across systems.
A significant part of the role is identifying and implementing AI and automation opportunities. You will use approved AI tools to accelerate analysis, generate first drafts, summarize trends, and improve self-service capabilities—always applying human review to outputs and decisions. You'll build lightweight automations, templates, and operating procedures that reduce manual effort and improve accuracy.
Operational support includes health and welfare, retirement, leave, and wellness programs. You'll partner with benefits vendors and internal stakeholders to investigate employee questions, resolve data discrepancies, and monitor service delivery. You'll support eligibility, enrollment, invoice, utilization, and renewal analyses.
Compliance and data integrity are critical. You'll support pay transparency, pay equity, and recordkeeping requirements; perform regular audits and reconciliations across HRIS, compensation, equity, payroll, and benefits systems; and escalate data issues, policy exceptions, and compliance risks promptly. You'll handle sensitive questions with discretion and manage multiple priorities in a fast-moving environment while maintaining high accuracy standards.
