Incentive Compensation Systems Manager | United States | Remote

Grafana Labs

2d•$144,000 - $173,000•Remote

About The Position

Grafana Labs is seeking an Incentive Compensation Systems Manager to join their Incentive Compensation (IC) team. This role focuses on driving the systemization, automation, and continuous improvement of commission operations. It's a high-impact, individual contributor role with end-to-end ownership, reporting to the Senior Manager, Incentive Compensation. The successful candidate will operate in an unstructured, fast-paced, remote-first environment, identifying process gaps, replacing manual workarounds with scalable systems, and enhancing the predictability, accuracy, and speed of commission, quota, and comp plan administration. The role offers deep exposure to incentive compensation data flow from CRM (e.g., SFDC) and People systems (e.g., Workday) through calculation engines (e.g., Xactly) to payout and reporting (e.g., BigQuery). This individual will be the go-to person for slow, fragile, or spreadsheet-dependent processes, partnering with IC Operations, Finance & Strategy, People Ops, and RevOps to streamline workflows. The role requires a blend of technical depth for automation and process discipline for problem prioritization.

Requirements

5+ years of experience in incentive compensation, sales operations, revenue operations, or a related systems/process improvement role.
Experience in a fast-paced technology or SaaS business is highly preferred.
Demonstrated track record of finding manual, broken, or inefficient processes and systematizing them, not just documenting problems but building the solution.
Hands-on SQL experience and comfort querying and reconciling data across systems.
Hands-on experience building automated workflows using tools such as scripting, workflow/RPA platforms, or ICM systems (e.g., Xactly, CaptivateIQ, Varicent, SPIFF platforms).
Comfort standing up lightweight tools or integrations when off-the-shelf options fall short.
Familiarity with core systems touching incentive compensation: CRM (e.g., Salesforce), HRIS, data warehouses (e.g., BigQuery), and comp management platforms (e.g., Xactly).
Strong communication skills, with the ability to understand team workflows and translate them into clear systems requirements and process changes.
Understanding of core comp mechanics (quotas, accelerators, SPIFFs, payout timing).

Nice To Haves

Experience working in a high-growth SaaS, cloud, or open-source company, particularly within a public company or an environment undergoing IPO readiness.
Proven success working within globally distributed, remote-first organizations across multiple time zones.
Experience documenting datasets and workflows for Model Context Protocol (MCP) server ingestion, or building AI skills/agents to automate incentive compensation data discovery, exception detection, or reporting.

Responsibilities

Embed with the IC team to map current-state workflows across plan administration, calculation, approvals, and payout.
Identify manual, repetitive, or error-prone steps and prioritize them based on risk, time cost, and business impact.
Design and build automated workflows, integrations, and tooling to replace manual processes, reducing reliance on ad-hoc spreadsheets and one-off scripts.
Serve as a hands-on owner of Xactly instances (Incent and Connect), configuring calculation rules, plan logic, and workflows.
Identify opportunities to use AI tools and LLM-driven agents for tasks like exception detection, data reconciliation, plan document review, or answering common comp questions.
Partner with IC, Finance & Strategy, People Ops, Revenue Operations, and IT/Data teams to ensure incentive compensation systems are properly integrated with clean, reliable data flow.
Establish clear documentation, standard operating procedures, and controls for newly systematized processes.
Set up a repeatable process for the IC team to continuously identify and retire manual work.
Act as the go-to resource translating IC process needs into system requirements and system/data constraints into practical process recommendations.
Support urgent, ad-hoc requests during payout cycles while focusing on systemizing fixes to reduce future fire-fighting.