This role will be based in San Francisco.
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
We’re hiring a Data Foundations Lead to architect and scale the core data foundations that enable trusted Finance reporting, automation, and operational decisioning. This is a senior individual contributor role that combines deep data architecture and governance expertise with cross-functional leadership. You will define the data operating model, build durable semantic and master data layers, and ensure quality, lineage, and controls are embedded end-to-end. This is not a dashboard-only role. You will build the foundations that make all downstream reporting and automation reliable, auditable, and scalable.
Responsibilities:
- Own the data foundations strategy for Finance: Define the architecture, standards, and roadmap for data models, semantic layers, and governance that power reporting and automation.
- Design and evolve governed metric and semantic layers: Standardize definitions, implement reusable logic, and ensure consistency across dashboards, automations, and data products.
- Build and maintain high-trust data foundations: Partner with Finance Technology and Engineering to develop curated datasets, lineage, and documentation that scale with the business.
- Embed quality, controls, and observability: Define quality checks, reconciliation routines, monitoring, and escalation paths to prevent and catch data issues early.
- Drive master data rigor: Align master data domains (cost centers, chart of accounts, suppliers, products) to governance standards that support finance workflows and analytics.
- Enable automation on trusted data: Collaborate with automation teams to ensure workflows and RPA are powered by governed data assets with clear access and controls.
- Lead cross-functional execution: Drive multi-team initiatives, manage dependencies, and set measurable success metrics and operating rhythms.
- Elevate decision-making: Turn data foundations into executive-ready insights through clear narrative, transparency, and adoption enablement.