Senior Product Manager, People Product

DoorDash is a technology and logistics company whose People Product team builds internal tools and frameworks for employee experiences across DoorDash, Deliveroo, and Wolt. The Senior Product Manager will own internal compensation products, including range-setting tools, recommendation engines, monitoring dashboards, supporting data products, and integrations with adjacent compensation systems. The role will lead product strategy, analytics, launches, adoption, and cross-functional partnerships with Compensation, People Analytics, and other teams.

Responsibilities:

• Own product decisions for the compensation range-setting stack — the range tool, its recommendation engine, and the monitoring dashboard — partnering with Compensation on methodology while owning how that methodology becomes product logic
• Define the data pipelines and data products that range setting depends on — historical ranges, offers, incumbent, and attrition data — and own the partnership with People Analytics on the semantic layer and the proposed compensation data mart, including what the product requires of each
• Own the range-setting product and analytics roadmap end to end and carry launches to market — adoption, enablement, and change management
• Improve Compensation Partner productivity across the range review, while also managing intake, prioritization, and requirements definition for this part of the compensation stack
• Own the seams into adjacent compensation products — recruiter offer guidance, budget modeling, headcount planning, and Workday range loads

Requirements:

• 5+ years of product management experience shipping products end to end, including at least one data- or workflow-heavy internal or B2B product
• Demonstrated success turning a manual, judgment-heavy operational process into a product — rules, guardrails, recommendations, and measurable throughput gains — rather than digitizing a spreadsheet
• Strong analytical skills and real comfort in data: you can size the problem, define the evaluation metric for a recommendation engine, read a precision-and-recall trade-off without flinching, and tell the difference between an anomaly and a statistically meaningful signal
• Experience shipping an AI- or model-assisted feature where output quality is the product: rule or prompt design, evaluation sets, and honest measurement against human decisions
• Excellent partnership and communication skills, including with the partners whose day-to-day judgment your product is encoding
• Experience working across custom-built tools and third-party SaaS (HRIS, ATS, survey and benchmarking, BI), including integrating data across systems and negotiating dependencies with platform and analytics teams
• Direct experience with Compensation or Total Rewards — range architecture, market pricing, survey data, compa-ratio, peer groups, leveling, or annual budget planning
• Familiarity with Workday, Greenhouse, Snowflake, and/or Sigma and their extensibility models
• Experience building for multi-brand, multi-region, and multi-currency environments, and the data-privacy constraints that come with them
• Experience shipping on top of a semantic layer, or enabling natural-language querying over a governed dataset